👋 Howdy to the 11,114 new legends who joined since our last edition! You are now part of a 371,144 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

🌱 A Day In The Life Of Ten CEOs. A collection of thoughts from a collection of leaders.
⚙️ Rebuilding Enterprise Operations Software. An interview with Wiley Jones, Co-Founder & CEO at DOSS.
🌊 TBPN, Vibemogging & The Future Of Trust. How technology media is changing and how you can ride the wave.

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No setup, just results.

Most people don’t struggle with tools—they struggle with knowing what to do next. (Or where to start!)

With seemingly endless possibilities within HighLevel, I found myself in that last category. What finally changed for me was discovering the 5 Day Challenge. Five days of learning the system and how to achieve some quick wins in my business gave me all the momentum I needed.

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HOUSEKEEPING 📨

I surprised myself this week. While being tired, sore, sunburned, and hungry, I managed to squat an (equal, I think) all-time front squat best of 135kg (around 300 lbs). My slow and steady trudge towards my lifetime lifting goals of a 120kg snatch and 150kg clean and jerk are well and truly still alive.

In other news, I find holidays kinda hard, especially ones like the one I am currently on, which involve sitting around, relaxing, and spending time with your thoughts. I guess it’s healthy? But, as someone whose mind runs at a million miles an hour, it’s been a challenge to slow down. What about you?

As I have gotten older, I’ve begun to think of myself as an athlete, just one that is competing in the sport of business and tech. And because of this, more of my time and energy (and money) is going towards training, recovery, health, and wellness. Maybe, I need to spend a bit more time in this low-stress mode to really allow myself to get comfortable, and give it time to sink in. Enjoy today’s piece!

INTERVIEW 🎙️

Bryan McCann, Co-Founder at You.com

Bryan McCann is the Co-Founder at You.com, the AI-powered search and research platform built to give enterprises reliable, real-time access to information across the open web. Before founding You.com, Bryan was a Lead Research Scientist at Salesforce Research, where he authored the first paper and holds the patent on contextualized word vectors; work that eventually led to the transfer learning revolution in NLP with BERT and other transformer-based architectures.

Bryan.

Bryan’s work stems from a deep philosophical interest in meaning and the desire to use AI to complement human creativity, inspire new thoughts, and develop tools for more fulfilling lives and a more complete understanding of the world. He holds degrees in Computer Science and Philosophy from Stanford, has self-studied Latin, and was more than once moved to tears by a mathematical concept. He is, in other words, exactly the kind of person you'd want thinking about what the internet should look like when the agents take over.

What’s the problem you're trying to solve with You.com? And why this?

As agents become more prevalent and there is a growing effort to have them do higher-stakes work and make higher-stakes decisions, the need for them to be trustworthy and reliable is increasing proportionally. The problem is that large language models, at the core of AI agents, are instantaneously out of date as soon as they stop training. So, until someone figures out continual training and continual learning, deployed models still need to call out to search and data APIs of various kinds, not only to provide information in a summarized, search-oriented way, but also to support actual knowledge work and agentic use cases. You wouldn't have expected a human, even ten years ago, to make high-stakes decisions for your organization without having access to something like a Google search to do some research and figure out what's going on in the world. You'd want them to have the freshest information possible.

So what we primarily do is crawl and index the public web, and provide an API for basic search. That basic search can then be augmented with the full contents of a page or key snippets from a page.

We can also loop in LLMs and our own agents to do deeper research, using those basic search tools as a fundamental unit, and then provide those results to our customers downstream. Zooming out a little bit, the biggest players like Google and Microsoft, that have well-established search indices over the public web, primarily use those as strategic tools to draw users into their own ecosystems. They don't really offer them as APIs for others to build on. Microsoft used to, but shut theirs down.

Search, but make it open.

Google never really did, though many people used third-party SERP APIs that would take a query, run it against Google, crawl the results page, and send those results back. But in that case, you're sending all your queries to Google, and some companies don't want to do that, especially in enterprise settings. If you're an AI lab that is perhaps competing with Google on foundation models, you really don't want to send them all your data, or you may simply need better reliability or the ability to handle more variable traffic. Large consumer-scale applications will have fairly continuous traffic, but if something goes viral, you need to be able to handle that kind of spiky behavior. Similarly, if you're an AI lab training a model, that creates spiky behavior too. So there are all these new use cases, and at the foundation of all of them is the idea that if more agents are doing more work than humans ever did, then they will be searching for information more than ever before. AI in its current form has not made search less useful or less important; it has actually amplified the importance of search, data, and all the other tools we build to support these agents.

Can you tell me about a real-world use case with a customer?

One great example is that we take a slice of our general web index, scoped specifically to the news domain, and serve all of the US news traffic for DuckDuckGo, a privacy-focused search engine that has been around for quite some time, and they rely on us for all of their news in the US. We are also doing a global expansion with them as well. Beyond that, many customers have adopted use cases around product research and competitive research, helping them understand where their own products sit in relation to the market, and what their competitors are doing in similar spaces. Some of these use cases fall into consulting or strategy-style research. Media and news companies also frequently use our APIs to do background research.

Source: You.com.

Hospitality is another interesting area. Players in that space need to establish some sort of independence within the open ecosystem, or risk facing the ongoing trend of Google (with Google Flights) and now ChatGPT, both presenting what could be an impending disruption for the independent travel industry, at least when it comes to bookings. The physical experiences underneath, of course, remain their own.

How would you describe You.com’s operating culture?

The team and the culture here revolve around a builder's mindset: a desire to take on significant ownership and responsibility. That means my org is filled with people who want to do more and take on more, which has been a real asset in keeping things fairly flat. Most people want to stay as close as possible to working with me or on the latest initiative, until they get their own big project where they can be the lead, make it their own, and grow and scale it. That has worked quite well for us over the years, and it has also allowed us to adapt fairly dynamically. We started out as a consumer-facing company and are now very much not just a B2B company, but an API company. The org has evolved with each shift in what we do.

Times Square'd up.

I often use the metaphor of building my organization the way you would build a neural network. You want good information flow up, down, and across layers. You might want skip connections, or what we'd call ‘residual connections’ in a neural network. It's really important to set the objective clearly so that the loss function—the error signal—propagates down through the network and drives change toward that objective, while the more fundamental layers remain more stable.

You.com customers.

I think that approach has helped us adapt fairly easily. One thing that has been particularly helpful more recently, and this may sound basic, is regularly revisiting the right grouping of people for each team, and clarifying which tools and metrics they own. As we've matured, that has become much steadier. What used to change every month, then every quarter, now perhaps changes every six months. We're trying to hold onto that nimbleness, double down on what's been working, and give ourselves more clarity into how the work should look going forward.

How does a company like You.com think about working with agentic coworkers?

The first thing is to have the mindset that you should use agents for just about everything. Many of our engineers have told me that they barely write new code anymore, that they're mostly interacting with Claude Code, or Cursor with Claude running, or something to that effect. Their time is already spent much more on thinking about what they should be doing to have impact, rather than on implementing and writing the code themselves. That has been a huge shift. A year and a half ago, I would have said we hardly used any coding tools, and people mostly thought they were great for boilerplate at best. Now, some people are not writing code at all. That has been very interesting to watch.

It has also been interesting to see how this extends beyond engineering. As a founder, I have been actively encouraging our sales and marketing teams to use these tools as well.

For example, every time we go into a customer conversation, the notes, the decks, everything should be much more customized and personalized, not only to that customer, but to that specific meeting. There have even been cases where I'm in a meeting with a salesperson and a customer, the customer asks for something, and I'm running Claude Code in the background so that by the time we're done talking, I can already show them a demo.

Source: You.com.

The mindset I try to instill is similar to something I carried over from my time in research: the goal was always to keep the GPUs running, because the more they're working, the more they're working for you, and the more you can learn and adjust your direction. It's the same idea here: always have something working in the background, and instill that mindset in people across every department, regardless of which specific agent they use. In terms of structure, it still primarily manifests as one-to-one: individual employees working with an agent to accelerate their own work. We don't yet have many multi-agent systems interacting across multiple employees, or anything more complex than that. I'm curious to see where that goes. It seems like multiple agents should eventually just live inside Slack, or whatever interface you use, but we haven't gotten there by any means yet.

Where do you think we'll be in five to ten years working with agents?

My time in research really embedded in me the idea that **data is king. My time at You.com, and watching AI have its moment, has only reinforced that, but I think I've extended the analogy a little bit to say that everything about a chessboard matters. Data is king, and AI is the queen on the board now. It moves around a lot and gets a lot done, but I think a company's strategy, or an individual's strategy, still revolves around the king—around data.

If you take that idea and apply it to what we're seeing with agents, knowledge work, and everything else, I divide people into roughly two groups. There will be people doing some form of work that generates data to train AI. And then there will be people evaluating that AI, either through actual benchmarks, evaluations, and harnesses, or in a fuzzier way, simply assessing whether it is good enough or strategically useful to them. Everything else will mostly get abstracted away. So you'll either be creating data for AI through your knowledge work—and most knowledge work will become some form of that—or you'll be on the evaluation side.

Engineers, for example, will remain valuable as long as they can produce code that is genuinely better than what the AI produces without them, in which case that becomes training data for the next iteration, until it no longer is. Or they'll be evaluating whether that's true and setting the direction in which AI should continue to learn. Even if you think of yourself as an AI manager or as a CEO of a swarm of agents, I would broadly categorize that as evaluating whether the AI is doing a good enough job and setting its direction.

How do philosophy, maths, and Latin shape artificial and human intelligence?

Mathematics probably has the biggest influence. Most of how I think about people stems from principles and abstractions I draw from some form of mathematics. I was at a philosophy group here in New York just a few weeks ago, and we were trying to discuss growth: how does growth differ from change, and various derivative questions that stem from that. My natural framing was to think about change in terms of metrics you can define and measure, and growth as some combination of a metric with a notion of accumulation. We talked about the example of a person who works really hard on themselves and seems to grow in this abstract human way until, say, a traumatic brain injury causes them to lose their memory. They grow after that too, but they're almost like a different person. Would you say the second version of them grew out of the first? It seemed like, perhaps not; that if their memory has a break in it, there's a discontinuity, and we might say they grew up until a certain point, that growth was continuous until the discontinuity, and then there is growth after.

We ultimately worked our way around to another framing entirely, but even the idea of continuity, and of topological spaces, whether we can separate two points in space in various ways, helps me understand things like quantum entanglement, or how people relate to each other and negotiate their relationships in business, work, and all aspects of how we socialize. So mathematics has been deeply influential.

Latin played a nice role too, particularly in my own understanding of language models. I found myself learning Latin mostly by reading it, essentially trying to predict the next word, in some sense. Latin has these clean prefixes, suffixes, and regular conjugations, much like other Romance languages, but even more simplified, and that mapped quite naturally onto ideas like word pieces, byte pair encodings, and how language models work.

Latin hits differently.

It also grounded me in an important problem in natural language processing: English is by far the dominant language in most training datasets, meaning many other languages—what we call low-resource languages—are underrepresented. Learning Latin and then reading texts like the Aeneid in that language made them hit differently. It genuinely convinced me that it is not as simple as just teaching language models a language like English. Even English itself is lossy compared to our full human experience, meaning it's lossy in how much you can truly understand the world through it. I had heard arguments that it would be wonderfully efficient if the world converged on a single language; no need for translations, no friction. But this experience convinced me otherwise. There is so much of another kind of meaning that we would lose in that process, and I'm really glad I came to understand that firsthand.

What book or idea has been most present in your thinking lately, and how’s it influencing You.com?

I really love some of the books by an author called Italo Calvino. He takes some sort of fantastical premise and then writes the story that follows as if it is completely normal and logical. Take The Baron in the Trees, for example: a young boy, for reasons stemming from his sister's unkindness, runs up a tree, hides, and never comes down. That's the premise. But the rest of the book is essentially: okay, what does that actually look like? Nothing else fantastical happens; he just never comes down. It turns out he inherits the title of Baron, acquires land, connects all the forests across that land so he can get around everywhere, and ends up meeting Napoleon Bonaparte along the way.

Source: You.com.

I love things like that because these seeds of fantastical ideas can turn out not to be that fantastical at all. Where we are today, compared to where I started in research, would have seemed pretty crazy back then. I wrote essays about it at the time because I thought I could see it coming, but it still felt so abstract. I think that's a useful lens for thinking about where we're going. I would also say that the concepts in the mathematical branch of topology have been increasingly important to me over the last several years. And perhaps most motivating of all is simply the reminder that we still know very little. That feeling of how much remains to be discovered, I find that particularly energizing.

How do you get the best out of yourself personally and professionally?

I'm going to emphasize the basics. When I was in research, the lifecycle revolved around deadlines, and you might sprint really hard around one of them. But when I found myself leading teams more, I realized it was more important to show up every day as the best version of myself, rather than sprinting toward a deadline and then being completely spent for a week afterward just recovering. So focusing on sustainability is key. That's not to say there aren't times when you push extra hard, but it's almost like you want to be constantly building up your tolerance and getting better, so that even those harder stretches don't seem as daunting. Sleep, eating well, taking care of your body and your mind, those things are extremely important.

I also think checking in with loved ones and friends, and staying connected to things outside of the professional world, remains incredibly important, especially if you're a founder. It's very easy to get completely sucked in, and even to genuinely love that. But it's nice to have triggers that pull you back out.

Bridging AI and outdoors.

Even if it means putting it in your calendar, scheduling a call with someone, or going to do that thing you know you used to love, just keep those things alive. That's how you run the marathon. And finally, making sure that you remain very human in a very AI-centric world is something I find helpful, too. I think that goes a long way in bringing back a sense of grounding when things get tough.

Extra reading / learning

• You.com’s CTO: An AI Visionary a Decade Ahead - June, 2025

• Bryan McCann on Productivity, Proactivity, and the AI-Powered Workforce - February, 2026

• Will AI Ever Create Its Own Meaning? - October, 2025

And that’s it! You can follow Bryan on LinkedIn or check out You.com on their website to keep up with what they’re building.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Vanta*—the security and compliance platform companies rely on to stay audit-ready without losing their sanity.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 7,108 new legends who joined since our last edition! You are now part of a 360,030 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

⚙️ Rebuilding Enterprise Operations Software. An interview with Wiley Jones, Co-Founder & CEO at DOSS.
🌊 TBPN, Vibemogging & The Future Of Trust. How technology media is changing and how you can ride the wave.
💰 Investing In The Intelligence Age. An interview with Mercedes Bent, VC Partner at Premise.

PARTNERS 💫

Investors don’t just listen to what you say. They look at how your company operates. The Fundraise-Ready Startup Kit equips founders with the materials investors expect to see, before the pressure is on.

• A scalable cap table template

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• Shift routine brand and marketing work out of product engineering queues.

• Run real marketing systems (CMS, SEO, performance optimization) with governance and collaboration.

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HOUSEKEEPING 📨

Landed in Bali a couple of days ago for a short week-long stay. The first thing I notice is that every time I go out to eat at a cafe, the one emotion running through me is anger. I am angry that I live in Melbourne, a city often praised for its great food culture, yet I can’t actually go out and find protein-dense, calorie-controlled, healthy food. I find it the same everywhere. It’s why, in the U.S., my favorite place to eat is Whole Foods.

This should be everywhere.

It’s honestly just a shame. People either eat a home-cooked meal or they eat poorly. Over here, every spot you stop at has the most nutritious food known to man. It’s a very sad state of affairs. Having said all that, I am excited to be here and to devour every beautifully healthy and wholesome meal in sight while I can.

COLLECTION 🏡

A Day In The Life Of Ten CEOs

There's a question I've asked every single founder and CEO I've interviewed for this newsletter. It's the same one you'd ask a friend if they landed some wild new job: 'So what do you actually do all day?' It sounds simple. It's not. Because the CEO role is the one job on Earth where the job description is whatever's on fire that morning.

How to not be a CEO.

I've collected answers from ten brilliant CEOs—from pre-seed to scale-up, from AI to media to fintech—and the range is genuinely fascinating. Some are deep in product. Some haven't written a line of code in years. Some have five direct reports, others have twenty. But there's a thread running through all of them: the best CEOs aren't optimizing for a perfect calendar. They're optimizing for impact on any given day. Let's get into it.

Des Traynor, Co-Founder & Chief Strategy Officer at Intercom

_{*Yes, technically, Des is not the CEO, but still interesting, and worth checking out.}

I work from our office about 95% of the time, unless I’m on the road. Most of my focus is on Fin, our AI agent for customer service. Each day starts with a stand-up meeting for the Fin leadership team, where we go over current customer issues, roadmap items, staffing, resourcing, and any key sales deals we need to be aware of or help push forward.

A big part of my day is reviewing Fin product work—new features, improvements, and iterations. Every 12 to 16 weeks, we run an event called Built for You. We had one about three weeks ago, actually, where we announced voice, a new Insights product, and also a replacement for CSAT, which we are calling the CX Score, and there’s always another one coming up.

Our next is in May. A lot of my time is spent figuring out what we’ll ship and announce at those events. The AI space moves so fast that we need to keep pace and meet the market where it is.

Outside of product work, as a founder, board member, and executive, I have a lot of other responsibilities: welcoming new hires, prepping for board meetings, and handling various high-level tasks across the business.

_{*To see our full interview with Oscar, head over here.}

Tim Huelskamp, Co-Founder & CEO at 1440

My day-to-day is constantly evolving, but at its core, it's about learning. I love learning, and so does our entire team. We're a knowledge company, so continuous learning and sharing are at the heart of everything we do. What makes the role exciting is that every quarter, every month, every week brings a new challenge. In the early days, it was about going from 78 to 500 subscribers. Then it became: how do we build a growth engine? How do we get our first dollar of revenue? Then it shifted to hiring the smartest people and building a great culture. Now, it’s about transitioning from a newsletter business—which will always be our core—to a full media platform. That’s a completely different kind of learning curve.

So for me, it's really about two things: staying in a constant learning mindset and making sure I’m focused on the highest-ROI initiatives for the company. I also want the whole team thinking that way. That means saying no to anything that doesn’t drive long-term value. No unnecessary meetings. No fluff. Even as we've grown from 5 to 22 employees, complexity has increased exponentially rather than linearly. So we work hard to keep communication clear, make sure everyone’s aligned, and avoid slipping into the bureaucracy you see at big companies.

We’ve actually taken a lot of inspiration from leaders like Brian Chesky at Airbnb and Jensen Huang at Nvidia; people who’ve built flat, focused, high-performance teams. That’s the kind of culture we’re working to maintain.

_{*To see our full interview with Tim, head over here.}

Patrick Thompson, Co-Founder & CEO at Clarify

Most of my time is spent working with customers and the internal team. A lot of it is about trying to be the voice of the customer. I'm a very external-facing person within the company. I spend a lot of time conducting customer discovery and interviewing people. I try to do the best job I can to relay that feedback back to the engineering team on what they're building.

A bunch of it's spent on hiring, too. A lot of it's been recruiting the best team I've ever worked with. So actively hiring, building the bench for when we want to scale the organization, managing fundraising, and managing investor relations. I think that's all pretty typical. I'd say the vast majority of my time is spent with customers, making sure that they're successful and that we're building the right product for them.

Team Clarify.

As far as the team goes, I have one other co-founder at the moment, Ondrej Hrebicek, who I worked with previously and who's our CTO. He's amazing. I wouldn't consider him a direct report; he's more of a peer, managing all aspects of the engineering side. Right now, I have five direct reports: one salesperson, a customer success manager, our head of design, a head of marketing, and a support engineer who just joined this past week. In addition, our head of operations reports to me. Looking ahead, I expect marketing and sales will continue to report into me, while product and design will likely be grouped more closely together. That’s probably the structure I see evolving over time.

_{*To see our full interview with Patrick, head over here.}

Oscar Pierre, Co-Founder & CEO at Glovo

Today, most of my time is spent on operations. A large part of that is dedicated to structured business reviews. Every semester, I define around 15 to 20 key topics that act as a proxy for our OKRs, and each one has a clear owner. We run monthly, documentation-first meetings for each topic, with detailed written documents and structured discussion. This cadence creates accountability, speed, and alignment across the organization.

Beyond that, my time is spent communicating with the team, hiring, reviewing performance, and handling ad hoc strategic and operational issues. I also see so much potential for Glovo to expand even now. We're looking towards 10x growth in the future. I see a big part of my role as sustaining a culture that is hard-working and driven. Maintaining that kind of energy and work ethic is vital if we are to successfully build the future of online commerce.

_{*To see our full interview with Oscar, head over here.}

Barbra Gago, Founder & CEO at Pando

As CEO, I’m building a people-focused product, so much of my day revolves around management, feedback, culture, and development. I’m constantly asking whether we’re creating a company that people love and living up to our vision. I dedicate significant time to sales and to product, because as a non-engineering solo founder, I wear many hats.

The product itself reflects my experience in people tech and my background as a CMO, and I spend a lot of time shaping the roadmap and engaging directly with customers.

_{*To see our full interview with Barbra, head over here.}

Bryan Murphy, CEO at Smartling

I like to start by saying that everything is my fault. I mean that both jokingly and seriously, because ultimately, the responsibility for how things go rests on my shoulders. My main job is to work with our stakeholders—our board, customers, and employees—to define our strategy and ensure we execute it effectively. That means setting both our long-term and short-term operating strategies and then ensuring the entire company is aligned around them.

I also spend a lot of time talking with customers. I believe strongly in what Jeff Bezos called ‘the empty chair’ idea, keeping the customer present in every discussion.

I do that both literally and virtually by staying in close contact with clients and with my team. Most of my time goes into making sure we’re focused on the right goals, staying accountable, and executing with consistency.

_{*To see our full interview with Bryan, head over here.}

Zach Lloyd, Founder & CEO at Warp

One of the great parts of being a founder CEO at an early company is that I get to do a bit of everything. What I focus on shifts based on what the company needs. Recently, I have been doing a lot of outward-facing work like podcasts, panels, and helping with sales. I also spend time shaping the product roadmap and vision.

Some days, I even write code or use the product myself. Overall, I look at each day through the lens of where I can have the most impact and do the most to increase the company’s chances of succeeding. What that looks like changes as the company grows and evolves.

_{*To see our full interview with Zach, head over here.}

Hussein Fazal, Co-Founder & CEO at Super.com

My day-to-day role as CEO revolves around a few core responsibilities. First, I set the high-level vision and strategy. With around 220–240 employees now, making sure everyone is aligned—from the exec team to the broader company—is crucial. That alignment starts at the top.

Second, I place a strong emphasis on talent. I’m involved in recruiting, especially when a hiring manager is on the fence about a candidate. I’ll step in and help close the deal because bringing in top talent is one of the most important things I can do. Third, I spend time thinking about the future, not just what we’re doing today, but what we’re building toward in two, five, or ten years.

Source.

We have a valuable membership program, and I’m always looking for ways we can add more value to it. Lastly, I spend a lot more time externally now. Talking to investors, managing the board, doing interviews, speaking engagements, and generally being the external face of the company.

_{*To see our full interview with Hussein, head over here.}

Jeff Seibert, Co-Founder & CEO at Digits

It’s bouncing between too many things—way too many things. The way I view my role, and this is my third startup, so it’s something I’ve evolved over 17 years of doing startups, is that my goal is to keep everyone unblocked and help anyone in the company who needs support. So I bounce between writing marketing copy, reviewing designs in Figma, and talking through technical architecture with our engineers. I still code a little. I spend a small part of my time fixing bugs in the code.

I try to be involved in everything across the company at what I call the 10% phase and the 90% phase. I want to be part of things early on, helping with the strategy, roadmap, and rough design, and then again at the end, polishing things before we ship. That could be the pixels, the copy, or whatever we’re putting out into the world. So my day is really just bouncing around the company, talking with people, and making sure things move forward.

_{*To see our full interview with Jeff, head over here.}

Luke Kim, Founder & CEO at Liner

My day-to-day job at Liner primarily involves two things: setting the strategy and building the team to execute that strategy. In AI, strategic thinking has become even more critical because if you’re just doing everything possible to survive, you might wake up one day and find yourself replaced by OpenAI. So, we’re careful about where we invest our time and focus.

Execution-wise, we constantly need to understand both our customers and the evolving technology. We essentially act as the interface between tech and the customer. Not many people can navigate this fast-moving wave well, so we look for individuals who are not only great at understanding both sides but are also good at learning and unlearning, because what’s true today might not be true tomorrow.

_{*To see our full interview with Luke, head over here.}

In sum

If there's one thing I took away from reading all of these back-to-back, it's that there is no single way to do this job. There's no CEO daily routine template you can download from some LinkedIn guru's Gumroad page (and if there is, don't buy it). Some of these founders are deeply structured: Thursdays for leadership, Tuesdays for one-on-ones, everything mapped to a cadence. Others are proudly reactive, bouncing between Figma, customer calls, and fixing bugs before lunch. Both seem to be working.

Me being proudly reactive.

The common thread isn't the calendar. It's the intentionality. Every one of these leaders has figured out where they specifically can have the most impact, and they've oriented their days around that. Not around what a CEO is supposed to do. Around what their company needs them to do, right now, today. And that's probably the most useful takeaway of all.

Extra reading

• Arctic Vaults, AI Agents & The Future Of Dev Tools - June, 2025

• Launching Athyna Intelligence - January, 2026

• Neighbors Feeding Neighbors, At Scale - February, 2026

And that’s it! You can also find all of our original interviews with all the founders and leaders above here.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting BILL—Your AI-powered financial operations platform.

beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 7,003 new legends who joined since our last edition! You are now part of a 352,922 strong strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

🌊 TBPN, Vibemogging & The Future Of Trust. How technology media is changing and how you can ride the wave.
💰 Investing In The Intelligence Age. An interview with Mercedes Bent, VC Partner at Premise.
⚡️ The World’s Hottest Industry: Post-Training. A look at the new industry taking the world by storm.

PARTNERS 💫

Lightfield is an AI-native CRM that just shipped Skills. Describe any workflow in plain English—account research, deal scoring, call prep, pipeline forecasting—and trigger it with one sentence. The AI agent learns how you work and runs the whole thing on command. 2,500+ startups already on the platform.

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• Ship pages and updates faster without turning the site into a fragile set of one-off hacks.

• Shift routine brand and marketing work out of product engineering queues.

• Run real marketing systems (CMS, SEO, performance optimisation) with governance and collaboration.

_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

I’m heading off on a one-week jaunt to Bali tomorrow, and looking forward to it. Not so much the Bali part; Bali is nice if you travel to the right places, of course, but just to chill out and do nothing for once. It’s not something that I get to do often, and my partner and I have a very nice villa with a pool, so the lounge chair is going to get an absolute hammering.

Ziggy and me.

It’s funny, I do definitely enjoy slower, less action-packed travel now compared to 10 years ago. Being 40 and being a decade into being a founder certainly ups the desire for doing sweet f*ck all, as we say in Australia. Anyway, we will keep releasing during my downtime, so don’t worry about that. For now, enjoy today’s interview!

INTERVIEW 🎙️

Wiley Jones, Co-Founder & CEO at DOSS

Wiley Jones is the Co-Founder & CEO at DOSS, an AI-native Operations Cloud that is rebuilding ERP software from scratch for companies managing physical goods. He studied mechanical and electrical engineering at the University of Illinois Urbana-Champaign before spending 18 months in China as a hardware engineer at Sprite Robotics, designing a robotic cat toy. It was there, watching a seven-person startup and iRobot's million-Roomba-a-year factory be equally strangled by the same rigid ERP system, that the problem crystallized. Back in Silicon Valley, he served as Head of Product at Athelas, where he watched medical providers manually comb through insurance claims because their systems were too inflexible to adapt.

Wiley.

He co-founded DOSS in late 2022 with Arnav Mishra, a former founding engineer at construction finance startup Siteline. The company has since raised $73M in total funding, including a $55M Series B co-led by Madrona and Premji Invest, announced in March 2026, with backing from General Catalyst, Theory Ventures, and Intuit Ventures.

What’s the problem you're trying to solve with DOSS? Why this?

We started DOSS a few years ago because we wanted to focus on a subset of the market that I think is pretty heavily underserved. These are companies that are managing physical operations in some shape or form. A lot of times, people call these product-based companies or inventory-based companies, but really, you can think of it as any business that's buying and selling some kinds of goods and then trying to get those out and distribute them to their end customers in the real world.

It's sometimes easier to disqualify what you don't help with, because it's such a wide and broad topic. But we tend to work with consumer goods companies (things you'd see in your grocery store or retail location), cafes, coffee companies, and construction businesses.

Viva Las Vegas.

We're helping them manage the procurement of items into their business, the flow of goods out to their end customers, and tracking the data and dollars that connect all of that.

We also tend to focus on the small to medium-sized companies; the meaty part of mid-market. We don't really sell into large Global 2000 or Fortune 500 enterprises. We're much more focused on serving businesses that are making somewhere between $20 and $200 million in revenue, when they're growing rapidly and trying to figure out the tech stack they need to operate.

What was the most difficult thing when going from zero to one?

The unique component of what we do—and I want to frame this as our experience specifically, not advice—is that we actually knew exactly what we wanted to do, and we were basically right about it each step of the way. We had very few deviations from what we articulated when we started the company to what we actually ended up building.

The hardest problem in a company like ours is being correct about the implementation details and not making architectural mistakes and product mistakes when you're working on something so wide and so deep, but also known. We're not going out and inventing a new foundation model. We didn't have to engage in cutting-edge state-of-the-art research, but we did have to build a lot of stuff relatively quickly and try to do it, making as few mistakes as possible. So it's very much a clarity of thought and execution game, and finding people who can operate at a very high level technically means it then becomes a recruiting game. You have to find the right people, put them in the right roles, and focus them on working on exactly the right things.

Christmas time with the DOSS crew.

I think it's easy to look at what we do and say you're just copying what's already out there and doing it better. But you do have to introduce quite a lot of novelty in how you synthesize these patterns to solve problems that are very poorly addressed in the market. In the case of inventory management, we had to build a system that's pretty composable so customers can adapt it to their actual needs, because supply chains are quite distinct. The standard approach in the market is extremely high levels of customization that can take years to implement. We found a few ways to make that a lot better and easier, but we were only able to do so because we had clarity up front about precisely what we believed the answer was.

Zero to one for us was about finding the right balance: having high conviction that we were right, executing for long enough to see the results through, and having the pain tolerance to go through each piece of that. Some companies have the exact opposite problem; they don't know what they want to do, they're trying to find sparks. We knew we were not in that boat. It was really just: carry the rock up the hill for as long as you can to the place where you can actually deliver on the vision you outlined at the very start.

How did you come to the SMB-to-mid-market ICP, and why not enterprise?

We didn't go in and sell to enterprises originally because they are qualitatively very different in what they look for in these products. You can make a decision early in your company's journey about whether or not you want to sell to very large lighthouse customers, use them as an amazing case study, build validation in the market, and then find a lot of other large enterprises like them. That totally works. But those companies will dictate your roadmap. They'll basically tell you what you need to build, and you'll lose a lot of control over the end product you deliver. You're designing each individual implementation around what these customers need you to do. It's just a completely different kind of company.

Download the report.

Our view was that we knew exactly what we wanted. We knew what we thought needed to exist, so go find the customers who have those problems and build the thing we want to build. When we first started, we were selling to companies doing five to $20 million in revenue, and as you mature your capabilities, you can move that window. We realized that the five-to-twenty range wasn't commercially strong enough, so we moved up. But we don't want to go above $200M generally, because the characteristics of what those companies look for when they do a full rip-and-replace of a system like ours. They're going to look for things we can't service today or don't want to, because they would be a distraction from the core business we're building.

Source.

Wiley and Co-Founder, Arnav.

It still comes back to the same answer: when you're defining your ICP, you either know what you want to build and who you want to serve, or you don't. If you do, you will make selective decisions. If you don't, you need to take what you've built and go figure out who wants it in its current form. And some companies don't need to be married to their ICP at all. If you're totally happy letting large enterprises dictate where you go with parts of your business, and it's directionally correct, who cares? It just totally depends on what you're building. The only clear, obvious answer is: don't try to do all of them. You have to be very selective and pick. Focus and energy are the only things a startup has a true advantage over a large incumbent; your ability to focus on solving a very specific set of problems. It doesn't have to be your ICP forever, but you need to start somewhere that is rigorously constrained.

Do you have a North Star metric?

I am not checking a single North Star metric. It's kind of a constellation. A single quantitative metric is not going to tell me how we're doing, and that's because of the stage we're at as a company. What I care about most right now is how many engineers we are hiring, what kinds, and what roles. Which individual leaders on our leadership team have been hired, and when they will be joining. There are probably three-ish leadership roles I'm currently searching for. And then there's literally doubling our engineering team, but inside of that doubling, it can't just be anybody. There are very specific qualities we're looking for. So on the talent side, I look at the inputs to that system and the outputs of it: how are we tracking over the periods of time we've been working on it?

Celebrating like top dog.

Then I'll look at marketing pipeline generation, sales pipeline getting worked, and closed-won deals. Same thing on the post-sales side: how are all of our implementations going? And then the same thing for product development and engineering: what are we actually shipping, when are things shipping, and how do those map to the workstreams I care most about? A single North Star metric is pretty useless to me. I'm much more focused on identifying the five to ten things that qualitatively have to happen in the company for us to be successful, and basically ignoring everything else.

What’s your recruitment strategy?

It depends on what you're looking for and what stage you're in. 60% of the company today consists of people who know others inside the company—it came through our network. Smart people want to work with smart people. And that's a horrible, basically useless piece of advice. It's like saying how do you get good at basketball? Get good at basketball, thanks.

Source.

What's more interesting is recognizing the stages you're in on your talent journey. When we first started the company, my co-founder and I did everything we could to find a few people who would get us to the next chapter, and we did everything possible to get them in. A big part of that is creating a narrative that gives people conviction in what you're doing. If I were like, ‘yeah, we're working on some stuff, and we'll see how it goes, that would have been impossible to recruit with. Instead, we wrote out a lot of our original product strategy, and we were spot on. We were off on the timeline by about four months from what we actually delivered. And when we articulated that to people back then—people we even tried recruiting who didn't join—some of them have now come on board, because they're like ‘these guys know exactly what they're doing’. They're calling their shot over and over again.

A lot of recruiting is about telling a story and making sure you're telling the right story to the right people at the right time, and knowing what part of the story you're actually in. If you're a super small company with two people and you're spamming mass outbound and putting up paid ads on LinkedIn for jobs, you will not get anyone. Stop. You're burning money.

Now, if you're at our stage today and going to double the team size in the next year, I can't be running every single recruiting process; that would be stupid. However, I need to be doing that for executive talent. My job right now is executive recruiting. I'm spending an inordinate amount of time with people who have been public-company C-level executives, mining their networks, asking, “Who did you bring up? Who's the best person who has ever worked for you? What are they doing right now? How do I get them to quit their job and come work for me?” Figuring out where you are in your talent journey is actually the single most important thing you can be doing as a CEO, especially for a show about CEOs. The CEO's job is to tell a really clear story, achieve internal clarity, and attract people to this mission at every stage.

What does an executive hiring process look like?

There's a process. It's actually pretty simple to explain and very difficult to do. Like our VP of Sales says, “Sales is extremely simple, very difficult.” Hiring is the same. You have to get to know these people. You have to understand deeply what motivates them, why they do what they do, what they want out of life, what they want out of this next chapter, where they're coming from, and where they're going, and you have to be on that path for them. Because anytime you're hiring executives, these people have optionality. If you're hiring the executive that no one wants, don't hire them. Good executives will be very hard to hire. If they're really easy to get, you should think carefully about whether you want them. It's basically just building a relationship predicated on you sharing a view of the world that they have to buy into.

For our company specifically, we only have true believers; we don't have tourists. There are a lot of companies that can get away with having tourists or mercenaries, and that's totally fine; it depends on what kind of business you are. Our business is way too hard for that. No one wakes up in the morning and thinks, "My God, I am just blessed. I get to work on enterprise-grade applications for supply chain management. This is the coolest thing ever." Now I do, but normal people don't. And the people who work here do, but no one here is normal. So you have to find people who truly believe what you're doing. That's us. Other companies need the high-flying geniuses, the deal guys, the 10x engineers who are mercenaries for hire. It just depends on what you do, knowing yourself, where you are, and where they are in their journey, and whether that fits.

How are you infusing AI into day-to-day operations at DOSS?

It's easy for me to spend a lot of time on it because I'm just so curious. It's consuming. And then what I do is really force people in our company to learn to do things differently.

A good example is our marketing and sales team. I have the whole company using Claude Code—and this was even months ago, before Anthropic skinned it and put Co-work on top. I was going to our sales and marketing team, showing them exactly how to start using it in their jobs. Even with someone on our marketing team who was asking about website edits, I just set it up for them and showed them how to use it. What kinds of questions would you normally ask me? Ask it instead. And now they're going in and making updates on how our CMS connects into the marketing site; something that normally an agency would be doing. Great, we fired our agency, because the people on our team can do it now, and they're actually faster.

Source: DOSS.

It's holding people's hands to the stove and saying, “We will do these things, here is how we do them, I will help you, and once I help you, you are enabled to go do it yourself.” I think people underrate the amount of energy and aggression required to drive an organization through change. Treating AI not as a tool, but as a way of working—thinking about it through the lens of people having to rewire how they work—has been extremely helpful in driving productivity in areas where it normally isn't there.

How do you get the best out of yourself?

Either you crack and crumble under pressure, or you get better at stuff. That's life. My wife and I had a baby about ten months ago. People were like, " You're insane, you have a small kid, and you're scaling a company. And I'm like, “Yeah, and it's fine.” This is what you do. This is all you got. If you're not going to go all out, what's the point?

It's extremely easy to get demoralized running a company, especially a company that's a pain sponge like this one, where the gratification is very long. This is not a company that goes viral.

This is not a company where you get an amazing hockey stick graph. This is a slow, chugging, methodical thing, and you have to organize your life around that if you want it to work. So then it comes back to: have the conviction and resolve to believe in yourself and take action accordingly. I'll go to my parents, my friends, my family, and I'm like, here's my stack rank: good dad, good husband, good CEO, good to myself, try not to gain twenty pounds.

And everything else below that, I'm sorry, I will not call you as much, but this is my priority list, and I have to be really aggressive about it.

I hear that a lot from other founders with kids who say it's just the same as having the company; it's just another thing, another slot of maximum commitment. And if you don't want to do that, if you want to have a company where you're like ‘hey, this is cool, I can work sixty hours a week, and I try hard, but it's not everything to me’; okay, great, hopefully that works. But I don't think that's that fun.

Extra reading

• $55M to Build the Operations Cloud for the Real World - March, 2026

• The Rise of the Anti-ERP ERP - October, 2024

• Lessons from Doss on building an ‘anti-ERP ERP’ platform

And that’s it! You can follow Wiley on LinkedIn or check out DOSS on their website to keep up with what they’re building.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Granola*—an AI-powered notepad that takes, summarizes, and organizes meeting notes without using intrusive recording bots.

beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 25,103 new legends who joined since our last edition! You are now part of a 345,919 strong strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

💰 Investing In The Intelligence Age. An interview with Mercedes Bent, VC Partner at Premise.
⚡️ The World’s Hottest Industry: Post-Training. A look at the new industry taking the world by storm.
🎤 The Speaking Skills Every Leader Needs. An interview with Tristan de Montebello & Michael Gendler, Founders of Ultraspeaking.

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_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

Caught the sassiest sausage doc / weiner dog / salchicha (depending on if you reside in Australia, U.S., or Latam) the other day. A long-haired, piebald coat, quite literally prancing her way down the street. I was lucky enough to catch her mid-prance, and she looked back at me. “This is my street, you’re just walking on it,” she said with her eyes.

Man, I love my dog. I am sure you do too, dear reader. It’s such a funny relationship; the relationship between a man (or woman) and his dog. The purest form of love in the world. Fun fact: my dog Ziggy, has his own LinkedIn. Go connect with him. And enjoy today’s post!

BUSINESS STORY 🗞️

TBPN, Vibemogging & The Future Of Trust

Today, my friends, tech media is changing. I had planned to write a story centered on the idea of founder brand and owned media, two of the pillars of our subsequent piece, but I couldn’t move forward without addressing the TBPN-sized elephant in the room.

For anyone who hasn’t seen tech Twitter in the last 72 hours, Sam Altman, with the help of the two men pictured below, absolutely vibemogged Dario Amodei, Anthropic, and the market at large. They stole the beating heart of technology storytelling. And for a rumored sum in the low nine figures (low and nine figures are at odds in that sentence).

Jordy and John from TBPN.

Why would a company as large and powerful as OpenAI want to buy a YouTube channel with fewer than 70 thousand subscribers? Two words: distribution and trust. Today, we will look at the TBPN deal, along with a handful of other examples of companies making a big push into the founder-brand and owned-media space. Let's dive in.

What’s happening today?

A penny has begun to drop inside of comms departments around the world. Today, more than ever, there is a voracious appetite for storytellers. Companies like Vanta, Ramp, Notion, and even Morgan Stanley are getting in on the action. Hiring a head of storytelling is certainly one way to go about winning trust in the marketplace.

I would argue, as I wrote in The Job Description Of A CEO, recently, that the head of storytelling should actually be the leader of your company. And I’m not the only one. Scott Galloway recently said, "I would bet within 5-10 years max, a key component of a board's decision to make someone CEO is how big their following is."

Source.

It might sound crazy to some, but it makes sense. Humans trust humans. We want to buy from people we feel would be reasonably comfortable having a beer with. It’s who we are, and it’s how we’ve always been. Taking a look at this example below from Airbnb’s 2023 Winter Release, with Brian Chesky’s personal post of the release doing roughly 100x more eyeballs from the branded account.

_{Note: This is a screenshot from a presentation I recently gave to the Startmate W26 cohort at Canva HQ in Melbourne. For the sake of time and energy, I didn’t bother to clean them up. And there are more, forgive me!}

It’s no coincidence that Stripe’s John Collison and Vanta’s Christina Cacioppo now host Cheeky Pint and Frameworks for Growth, respectively. Yes, it’s content, yes, it’s distribution, but it’s so much more than that. This is the evolution of founder brand → founder media. The ultimate parasocial relationship.

Source.

Source.

Take a typical sales funnel, for example. Most companies are out there running countless channels to get in front of their audience. This starts with generating traffic and building awareness. Think Meta Ads, Google, too, trade shows, events, podcast sponsorship, and creator partners. Every brand needs people to know they exist. Next is the middle of the funnel: email nurture campaigns, case studies, and social proof marketing, blah, blah, blah. The final stage of a good sales funnel is the hardest. Trust.

But what if we were to flip that on its head? What if we led with trust? ‘John Collison, he seems like a good guy, I could definitely grab a pint with him,’ or ‘Geez, I love Frameworks for Growth, this Christina seems really, really smart.’ This totally hijacks the funnel, putting trust up front, and opening the door to a much smoother sales process.

The data backs this up. 63% of consumers in the U.S. are more likely to buy from someone they follow, and 57% more likely to recommend them. Find any dataset online, and it will tell you the same. Your ape ancestors were not going to be swapping bananas on the savannas with an untrustworthy primate. Our little monkey brains were evolved to partner with and do business with people we trust.

Who is doing this well today?

There are a handful of scale-up founders leading the way, building trust and, in the case of our next example, goodwill, across the ecosystem. Take James Hawkins of PostHog, who has grown his brand by becoming the ultimate techno-shit-poster. His style of building trust is through comedy and not taking himself too seriously. This works because it aligns super well with PostHog, which is one of the most unhinged brands in tech.

Source.

PostHog is also playing in the owned media space, similar to our examples of Stripe and Vanta, but in this case, with their newsletter, Product for Engineers. The newsletter focuses on how PostHog builds product, but also covers general technical concepts and is written by a handful of team members, one of whom is James himself.

Product for Engineers.

I spoke to Ian from PostHog recently about this strategy, and he told me, “We’ve spent countless dollars on Meta and Google, along with newsletter ads; the only thing that converts is our own newsletter.” Again, trust over time builds the relationship with the reader until they are ready to buy.

Another founder I like following is Tyler Denk. Tyler leads beehiiv, and also has a strong presence online, although if James’ brand archetype is The Joker, then Tyler’s is definitely The Rebel. He enjoys starting a fight with competitors online, and one of the better things you’ll see is the community—present company included—going in to bat for him.

Again, as in the previous examples, Tyler is building trust in the most impactful way possible through his newsletter, Big Desk Energy, which is a weekly build-in-public-style essay on his experience building beehiiv, now read by north of 100,000 people.

Another example is this very newsletter, Open Source CEO. My team and I at my startup, Athyna, made the bet a while ago that if we could build my brand through socials and, more importantly, this newsletter, it would go a long way in opening doors in the future. Take this reply from my Neumannomics piece from Phillip Moyer.

At the time of the reply, Phillip was the CEO of Vimeo. Not a bad ally to have, really. Especially, knowing that the base level of trust is likely to be there if I ever need it.

Are you a trusted voice? Or are you a slop cannon?

Here's something nobody likes to admit. The same tools that make it possible to build a genuine founder brand are also the ones companies use to fire an absolute tsunami of content-shaped garbage at the internet.

Before the internet, content was scarce. There was a floor on quality because there was a cost that came with publishing. After the internet arrived, that floor dropped out, and volume went through the roof. We got a lot more great stuff. We also got a lot more garbage. In 2026, the curve doesn't just grow, it explodes. And it explodes mostly to the left. We have officially entered the slop cannon era.

Source: Uncharted Territories.

We have entered a world where anyone can produce more content in a day than most companies used to publish in a month. A world where the volume of ‘thought leadership’ being fired at LinkedIn on any given Tuesday would have filled a library in 2005. Most of it has no soul. No opinion. No personality. No trust.

Here's the thing, though: The more slop that gets fired into the world, the more valuable a genuine voice becomes. This is the counterintuitive upside of the AI content explosion. Real trust is getting rarer and more powerful at exactly the same time it's getting harder to fake.

James Hawkins doesn't have 5.2M views on a Microsoft Teams meme because he has a great content strategy. He has it because he sounds like James. Unmistakably, irreducibly James. That's what cuts through. That's what you're actually competing for. Not attention. Trust.

Your options: Build, buy, partner

Now that we know the lay of the land, it’s important for you to know your options. As with all good opportunities, you should look at it through the very simple framework of build, buy, or partner. Let’s look at each of the options in reverse order.

Partner

This is the lowest-friction entry point. You're not building from scratch, and you're not writing a cheque with nine figures on it. You're borrowing someone else's trust. This is what our sponsors in Open Source CEO are actually doing. When Vanta, Granola, or Framer shows up in this newsletter, it's not just an ad placement. It's a trust transfer. 345,000 people who trust me now have a reason to at least look at your product. You didn't necessarily earn that trust. You borrowed it.

In the example of this newsletter, I also work as an outsourced storytelling lead to trusted partners. Vanta has run multiple campaigns in a row now, and keeps coming back to have my document the company. I have done the same with Attio, Paddle, and more.

Source. Source.

Source. .

This works because my partners know that my audience trusts me and believes me when I write about a company. Partnering is a great place to start, and most brands stop here. But there are two more levels to explore.

Buy This is the OpenAI/TBPN play; HubSpot buying The Hustle before it, and Robinhood acquiring MarketSnacks before that. You write a big cheque. You acquire an existing audience and, more importantly, an existing relationship. The trust is already baked in. Fastest path to distribution, full stop. But here's what people miss about these deals. The real asset isn't the content. It isn't the subscriber count. It isn't even the channel. It's the trust the audience has in the creator, specifically.

Audiences follow people, not brands. If the talent walks out a year after the acquisition, the trust walks with them. But if you have the capital and the patience to integrate without destroying what made it valuable in the first place, this can be a huge win. The most successful example of this working out in recent memory is Hubspot, and how they have managed to keep Sam and Shaan engaged on the My First Million podcast (part of their acquisition of The Hustle).

Build

This is the true long game. A newsletter. A podcast. A YouTube channel. Starting from zero, and compounding over time. There is no cheque required here, just consistency and the willingness to keep showing up before anyone is watching, and everything feels shit.

The key here is putting a genuine human voice at the front of your company and giving them room to actually speak. Vanta didn't build Frameworks for Growth because they needed more content. They built it because Christina Cacioppo is interesting, and people in the compliance and startup world will pay attention to her in a way they will never pay attention to a Vanta product page.

Slim to no relevance here.

Same with Stripe and Cheeky Pint. John Collison having an honest conversation with Satya Nadella is worth more to Stripe's brand than a hundred press releases. It's the trust-first funnel, built from the inside out.

Case Study: The TBPN deal

Now, we finish with the aforementioned TBPN deal. On April 2nd—less than 18 hours post the April Fool’s safety window of noon on April 1st—the team announced that they had been acquired by OpenAI. This took the business and media space by storm, sending Twitter into a fury of takes about how this affects the future of media, and how budding creators can snap up TBPN’s pre-exit sponsors.

On paper, a deal rumored to be in the low nine figures for a channel with just over 50,000 subs sounds mad. But it is not without precedent.

Source: NY Times.

As recently as October of last year, the Ellison family (David, with his father Larry’s money) snapped up the center-right business and politics brand, The Free Press, for an eye-popping $150M. A large sum for a brand with a relatively small audience.

And while TBPN’s advertising arm reportedly generated $5M in revenue in 2025 and had a run rate of ~$30M this year, OpenAI plans to wind down the advertising side of the business entirely. If rumors are true, they purchased a media brand at 10x year-end revenue projections, only to shutter the ad sales. So, why buy it? Well, similar to the acquisition of The Free Press, it comes down to one bone-smashing inspired word: Vibemogging.

For OpenAI, it’s been a horrible year. They are hemorrhaging cash, they shut down Sora, and the deal with the Pentagon made them look like the shit-eating bad guys. More importantly, for many months now, the only real word on the street is how much better Claude is for most things: coding, writing, automations. Claude Cowork’s release was the nail in the coffin. Every man, woman, and child has moved from OpenAI to Anthropic if they weren’t already there.

One way to counter all this negative press is to buy the most consequential up-and-coming technology show, TBPN, effectively vibemogging Anthropic in a cultural watershed moment for tech.

Source.

Now, OpenAI, through their new media-mogul employees, John Coogan and Jordi Hays, gets to trustmaxx by association. People think this is just about distribution, but it’s not. It’s about repairing and building upon their deteriorating brand.

Summary / Future

The smart money has stopped betting purely on products. A seismic shift is underway in how companies build credibility, and the TBPN deal is the moment it went mainstream. Owned media, founder brand, and earned trust have quietly become the most defensible moats in tech, and the companies moving now are locking in an advantage that money alone can't replicate later.

Source.

For founders who can't write a nine-figure cheque, the path forward is the same as it's always been: start building your voice, consistently and authentically, before you feel ready. Partner with trusted voices in your space. Document the journey. The person who plants that flag today and keeps showing up before anyone is watching will be nearly impossible to catch in three years. The future belongs to the storyteller.

Extra reading

• The Perfect Onboarding In 7 Simple Steps - May, 2024

• How (This & Other) Newsletters Make Money - November, 2024

• A Guide To Crafting Your Brand Voice - December, 2025

• How Athyna Makes Remote, Work - March, 2026

And that's it! You can follow me on Twitter and LinkedIn, and also don’t forget to check out Athyna while you’re at it.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Lightfield*—an AI-native CRM that assembles itself from your email, calendar, and meetings.

beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 7,498 new legends who joined since our last edition! You are now part of a 320,809 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

⚡️ The World’s Hottest Industry: Post-Training. A look at the new industry taking the world by storm.
 🎤 The Speaking Skills Every Leader Needs. An interview with Tristan de Montebello & Michael Gendler, Founders of Ultraspeaking.
👏🏻 The Invisible Layer Separating Good AI From Great AI. An interview with Tyler Phillips, AI Product Lead at Apollo.io.

PARTNERS 💫

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From the inventors of AI sales roleplays. Training only matters if it shows up on real calls. Hyperbound gives reps a safe place to practice tough conversations and gives leaders visibility into the skills that actually move pipeline.

No guessing. No extra meetings. Just sharper reps, better calls, and more confident forecasts. Want to check it out yourself?

_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

One of our most recent and super-active sponsors, Framer, just dropped their State of Sites ‘26 report. If you are like me, you are probably a total nerd for anything that you think can unearth an insight or two to help you grow.

Download it here.

And now that half of the internet is shipping epic sites on Framer at lightning speed, this report does just that. Honestly, though, I’m a sucker for a gradient, so it’s worth downloading the report for the design alone. Now, let’s dive into today’s piece. I hope you like it!

INTERVIEW 🎙️

Mercedes Bent, Co-Founder at Premise

Mercedes Bent is the Co-Founder of Premise, a new VC firm. She was most recently a partner at Lightspeed for 6 years, leading investments in AI, consumer, fintech, and saas. She was named one of 9 Rising Stars in Venture Capital by the Wall Street Journal and has invested in multiple early-stage companies. Prior to joining Lightspeed, she was a GM at General Assembly, where she helped grow its revenue from $2M to $100M in 4 years, and worked as an analyst at Goldman Sachs. She has an MBA and a Master's in Education from Stanford University, and an AB in Economics (Behavioral Economics) from Harvard University.

Mercedes.

Today at Premise, she invests in products that feel magical on first use, spread bottom-up, and become defensible through system design (networks, platforms) or embedded workflows and their accumulated data advantage (like a system of record). These founders obsess over product craft and ship fast. In this conversation, she shares her unfiltered take on where we are in the AI cycle, what creates real competitive advantage in a world of cheap models, and why the quality of the founder is everything.

Where do you think we are in the AI cycle?

I think we're in a period where there has been a ton of excitement about what can be created. We get to experience amazing products like ChatGPT or Claude, and people can see the possibility. At the same time, we haven't had a lot of truly revolutionary experiences created yet, and there is also tons of fear from the mainstream public around job and income loss.

We're also still figuring out what the right unit economics look like, and whether there's a way to make this economy work affordably. Right now, there's a lot of cost structure going into debt to service CapEx investments, and we're not yet sure if the unit economics work.

I think we're in a pre-security phase of AI, where AI is writing a great deal of code, but we aren't yet fully aware of the security vulnerabilities we're being exposed to as a result. Another way I would characterize where we're at is by drawing a parallel to the dot-com boom: are we heading toward a bubble? I think we're still in the 90s and haven't hit 2000 yet.

There's a lot of promise, but also a lot of potential risks we don't fully understand, and the economics remain unclear. I think we're in the hubris part of the adoption cycle, and I worry that we're not going to get a lot of these answers figured out soon. We'll just keep piling on more and more investment. Maybe that's actually a good thing, that we'll invest through the uncertainties, but there is immense uncertainty right now: hubris and uncertainty.

What's the biggest shift you're seeing in AI startups that actually matters?

One big shift I've seen recently is that AI startups are increasingly focusing on distribution much earlier than before. Because the cost of production and building great products has come down so low, you can now use tools like Lovable, Cursor, GitHub, Claude Code, V0, or Gamma to create great experiences. Builders are dedicating a lot more attention to how to get distribution quicker. There used to be a saying that ‘first-time founders focus on product, while second-time founders focus on distribution’. The idea was that it took an entire second company before you realized that distribution is actually the hard part of building a business. I'm now seeing that change, with people figuring out distribution much earlier in the process.

Mercedes in action.

What a team!

I think this also dovetails with the fact that we have a chronically online, influencer-first generation that grew up with YouTube. These are the same people who are now entering the workforce, building companies, and who, ten years ago, said the number one job they wanted when they grew up was to be a YouTube influencer. So I think it's a confluence of things: a social media generation that grew up understanding how important it is to have a brand and a following, combined with the fact that the cost of making products has gotten so much cheaper and faster, freeing up more time to dedicate toward distribution.

That's one of the biggest shifts I've seen across the spectrum. I do still worry that there is a lot more depth that needs to go into building products that are being a little underappreciated. And circling back to something I mentioned earlier, another shift that hasn't happened yet but needs to is that there isn't enough focus on security going into the building of these products.

What are the most common mistakes you see in founders when pitching AI companies?

I believe a lot of founders are not architecting their business model to be long-term defensible from day one. In the beginning, I do think what you need to do is ship as fast as humanly possible: create a lot of output, and really, the only moat early on is the speed at which you ship features. But that phase is increasingly giving way to the next one, where you have to build a durable, defensible business model.

The most defensible business models are networks, platforms, and systems of record. A network, like a marketplace, is one where each additional person added makes the product stickier and more valuable for everyone. A platform is something like Apple's App Store, Steam, Unity, or even Roblox, where third parties monetize and get distribution through your platform—they gain access to a new set of users, but have to conform to your tools and ecosystem to make it work. A system of record is where critical data lives, like Flo for period tracking, or larger companies like SAP, Oracle, and QuickBooks. These are the businesses people can't leave because their most important data is stored there.

One of the mistakes I see is that founders don't put enough intentionality from day one into architecting a business model that compounds over time (one that gets better and more defensible the more you build and invest in it). Many times, you build based purely on what customers want, or a problem you felt yourself, which is valid. But increasingly, I think you have to start thinking four to five years ahead and asking: what is the business model that will perform best in the long run?

What creates competitive advantage for AI firms as models get cheaper and powerful?

I think your competitive advantage always has to do with what the founders' greatest strengths are. Everyone is good at something different, and what you want to do is find the thing you're best in the world at and go really deep there. It could be something technical in the architecture of the product, it could be a new go-to-market approach you've invented, or it could be your ability to tell stories and craft a narrative that is stronger and more compelling than anyone else's. Those are the right areas to focus on.

Source.

Always backing exceptional founders.

The way to think about it is: what am I best in the world at? Find that atomic unit of competitive advantage and draw concentric circles around it; meaning, deepen your advantage over and over again until it starts to compound. That, to me, is how you find and build a true competitive advantage. To get there, you almost have to take stock of yourself, and sometimes that means asking other people what is uniquely special about you relative to everything else they've seen. Often, you're not fully aware of what it is yourself, but other people can usually see it quite clearly.

How has AI changed what you look for in founding teams?

I've actually started looking a lot more for technical founders. This might seem counterintuitive, but even though we have so many more tools available to create products, I think that also means a lot more people can make bad products.

So I'm even more interested in people who truly understand how things work—down to the computer science level, down to the zeros and ones, the rails and the bits—and who know how to build elegant, secure computer systems. Having that technical depth is extremely important to me. That's probably something I flipped on in the last two to three years: I won't invest in a team anymore unless I believe they have real technical prowess and depth.

Source.

The other shift is more a reflection of where I am in my own investing journey. I started a new venture firm, and I'm now investing at the pre-seed and seed stages, which means I'm going in earlier than before. At that stage, it really comes down to the quality of the founder. It's not that I didn't invest in quality founders before, but the shift is that I now place roughly 90% of my investment thesis on the quality of the founders themselves.

How has your experience shaped the way you evaluate companies?

A lot of what goes into evaluating companies is knowledge you gain from being an institutional venture capitalist—I actually think institutional VCs are much better at evaluating companies than operators. It's not necessarily a skill set you learn from operating. That said, one thing I would point to on the evaluation side is that from operating, you learn to better understand what's real versus what isn't when a company delivers materials from a data room perspective. You develop a sense for what systems and data they might actually have access to, and what the fidelity of that data looks like. A lot of founders are not nearly as clean in their tracking of data systems as they should be, and if you ask for a lot of data, they simply can't produce it. That's something I know from being on the operating side.

Source.

But the bigger lesson I took from operating is really about how I run my venture firm. When I was an operator, the way you stayed at the edge of your field and at the forefront was by following and having access to the people who were also experts at the forefront of their fields. That requires having a community and being able to learn and trade notes with one another. So what we built for our new venture firm is a series of communities focused on technical founders, engineers, researchers, product managers, and designers. We run a monthly event series called Surreal, and we created a WhatsApp group where people can discuss things like the efficiencies between Claude Code versus Cursor, or how to set up a multi-agent MCP system.

Creating that kind of space and community is something I learned most from operating, because I know how vital it is when you're building on your own to have access to the right people. Operating is actually a very siloed game; you are focused entirely on your own problem, and it's really hard to pick your head up. Venture, on the other hand, gives you an incredibly wide breadth and access to a vast network of people. I wanted to create a place where founders could pick their heads up and have access to the best people around them.

How do you get the best out of yourself personally and professionally?

If I had the answer to this, I would be winning at life! I do think that mastery of self is one of the hardest things we have to conquer—that's the whole point of life in a way, isn't it?

On a practical level, I try to get eight to nine hours of sleep, exercise regularly, drink water, eat healthy, and talk to friends. Those are the basics of maintaining good mental health and sanity. Honestly, though, I work way too much to be doing great on all of those factors all the time. But if I had to give a real answer, I think it comes down to this: you are truly a product of the five people you spend the most time with.

The best way to get the best out of yourself is to make sure that those people are the highest quality people you could surround yourself with. It's almost an outward approach to self-improvement: bettering yourself by being intentional about who you let into your inner circle. I think we have to be really conscientious about who we spend time with and how those relationships shape and improve who we are.

Extra reading / learning

• VC Mercedes Bent says it took a year of meetings to land a job at Lightspeed - January, 2021

• How learning velocity can make or break a startup - May, 2024

• The Mindset of a Top-Tier VC with Mercedes Bent - September, 2025

And that’s it! You can follow Mercedes on LinkedIn and X to keep up with what she’s building!

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Framer*—the site builder trusted by startups to Fortune 500.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 2,584 new legends who joined since our last edition! You are now part of a 313,311 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

🎤 The Speaking Skills Every Leader Needs. An interview with Tristan de Montebello & Michael Gendler, Founders of Ultraspeaking.
👏🏻 The Invisible Layer Separating Good AI From Great AI. An interview with Tyler Phillips, AI Product Lead at Apollo.io.
🚴 Fundraising Fatigue, Hypergrowth & Selling Glovo. An interview with Oscar Pierre, Co-Founder & CEO at Glovo.

PARTNERS 💫

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You jot down what matters to you and, in the background, Granola transcribes the meeting.

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First impressions matter. Launch a production-ready site in hours with Framer, no dev team required.

Early-stage startups get one year of Framer Pro free. No code, no delays. Scale from MVP with CMS, analytics, and AI localization. Trusted by hundreds of YC-backed founders.

_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

Had a nice little Melbourne newsletter-nerd lunch this week, as part of my decision to try and meet more people across the business and tech ecosystem. As someone who has had crippling anxiety since a traumatic brain injury 12 years ago, it’s pretty hard to live a normal social life. All the things most people think come easily just don’t. But I’ve been building my tolerance for social settings back due to exposure therapy.

Creator crew.

I started with one single catch-up per week, then two, then three, usually with one person, in the morning, or sometimes before lunch, when my anxiety is much easier to navigate. I’ve graduated to a handful of meets per week, sometimes later in the day, with up to three people. I even went to a loud bar the other day for a beer with a mate. Things I’d not have really considered in the last five or six years. Anyway, nothing else to share really, but shoutout to you out there who go through the same struggles. As an old psychologist of mine told me, “It’s better to live life scared than not at all.” Onwards!

BUILDING IN PUBLIC 🔎

The World’s Hottest Industry: Post-Training

Through the 1840s and 50s, more than 300,000 people flooded into California to mine gold. Most didn't strike it rich. The real winners were selling picks, shovels, and jeans (hello, Levi Strauss). This moment in time basically gave rise to the San Francisco we know today. That same San Francisco that, 175 years later, would see a similar flood of capital, human and otherwise, into the city to run headlong into the newest opportunity: artificial intelligence.

To create intelligence at the human level is evocative, above is scary. Orders of magnitude more intelligent—a place most futurists assume we’ll get to sometimes in the next few decades—is downright science fiction. On the one hand, AI could disrupt every industry, displace millions of jobs, and cause social upheaval. On the other hand, it could lead to breakthroughs, from solving sustainability problems to extending the human lifespan to curing cancer.

Trust me, friend.

Whether you think we’re heading towards a future utopia or something much darker, the one thing we can agree on is that there is no stopping this freight train. It’s the modern-day gold rush. The boom of our time. Interestingly, there is one industry, data labelling and post-training, that is growing faster than any other area on earth today. Companies that can help foundation model players, along with their application-layer counterparts, train their models to be smarter, faster, wittier, and more accurate are in short supply. Those that do exist are growing at an incredible pace.

Today, I plan to take a moment to demystify a sector of the industry that functions as the engine room to every AI company on the planet. So buckle up, fuck knuckle, we are going to hyperspace today.

Party at the front

Before diving headfirst into this, I’d like us to acknowledge what the front of house of AI looks like. We’ve all seen it; companies growing at a pace that we’ve never seen before. But it’s not just revenue. They are getting founded and funded like never before. The average SaaS founder is now snickered at in VC circles like an agency business model in years past.

Source: Repoint Ventures.

Source: Repoint Ventures.

Although OpenAI still takes the lion's share of headlines—especially for its ability to raise capital—Anthropic seems to be pulling ahead in the LLM race today. They have grown revenue 10x in the last three straight years, with many projecting they overtake OpenAI sometime between mid-2026 and early 2027.

Source: Anthropic.

Source: Epoch AI.

But this piece isn't about the models themselves. It's not about the chatbots, the copilots, or the shiny new AI wrappers getting funded at 100x revenue. This piece is about what happens behind the curtain. The engine room. The bit that makes all of the above actually work.

Because here's the thing nobody wants to talk about at the AI cocktail parties: every single one of these models—ChatGPT, Claude, Gemini, Grok, Llama—needs to be taught. And teaching, as it turns out, is now a multi-billion-dollar industry growing faster than anything else on the planet. Allow me to explain.

How AI actually works (an idiot's guide)

My brother just had his first child. Yep, that means I’m an uncle. Go me! And that child, my nephew Sidney, will feature in the following analogy. You see, there are a few stages that an AI model goes through, very akin to how a human makes their way through the world: failing, learning, growing, adapting. Let’s take a look at these stages for a moment.

Stage #1 - Pre-training (birth through school)

The first stage a model goes through is equivalent to the stage young Sidney is at today. This is where the model is in its heavy-duty information-gathering mode.

For Sidney, it’s learning that bipedalism is awesome, and shitting your pants is only fun for a short while. For our LLM, this is where the model reads the internet. Basically, all of it, good parts and bad. Wikipedia, Reddit, textbooks, news articles, GitHub repos, obscure tweets about whether a hot dog is a sandwich, and whether the deep state cloned your favorite celebrity. Trillions of words, consumed in a matter of weeks by a data center the size of a small town.

Sidney and his dad.

And while Sidney is still really at the ‘da-da’ and ‘ma-ma’ stage, so is our LLM. It’s mapping the world, and learning the patterns of language. Soon, Sidney will understand that ‘yum yum’ means food, and that ‘dada’ is often followed by ‘loves me.’ Words will begin to link up. Same thing for the models. Grammar, facts, reasoning, vibes. By the end of this stage, the model is like someone who has read every book in the library but has never had a conversation. Technically knowledgeable. Socially useless.

Stage #2 - Fine-tuning (the internship)

Sidney may have the cerebral horsepower of a turnip at the time of writing, but it will not always be that way. As he goes through school—so long as he doesn’t get expelled multiple times like his rebellious uncle—he will learn all the basics of life. He will read books, learn maths, build and paint things, and when he’s ready, even ask a girl out for the first time. But school is not real life.

_{*Note: I am including this School of Rock clip for no other reason than it’s awesome. Enjoy.}

The same goes for our models. They have learned, but not tried to apply any of their learning to outputs. Now it’s time to take our well-read-but-awkward model and start shaping it. You show it examples of good behaviour: ‘When a human asks X, a good response looks like Y.’ This is where the model starts to feel like a product. It learns to follow instructions, format its answers, and aims to be helpful rather than just technically correct. Think of it as the difference between a university grad who knows everything about accounting and one who can actually file your taxes.

Stage #3 - Post-training / RHLF (the real world)

This is the moment that young Sidney, along with our LLMs, finally grows up. For Sidney, that might mean a quick gap year trip to Trinidad and Tobago (I hear it’s nice), followed by the first steps towards his future career. He'll get his first real job, make mistakes, get feedback from a boss who actually knows what they're doing, and slowly get better. That's exactly what happens to the model. For our LLMs, this is where humans—real, living, breathing humans—sit down and evaluate the model's outputs.

’This answer was better than that one.’

’This response was accurate, but the tone was off.’

’This code compiles but has a subtle bug on line 47 that would crash a production server.’

The model learns from this feedback in a loop: generate → evaluate → improve → repeat. It's called RLHF (Reinforcement Learning from Human Feedback), but what it really means is: humans in the loop, making the machine less stupid, one correction at a time.

The thing nobody wants to say out loud is that models are converging. At the first two stages of our story, all the AI models train on the same data, optimized toward the same benchmarks, and for the most part, the gap between them has closed. The real differentiator now is stage three, expert human feedback applied to actual workflows.

Father of newly-crowned nepo-media-Jesus, David Ellison, and technology mega-chud, Larry Ellison, said the quiet part out loud at a recent Oracle event: models like ChatGPT, Gemini, Grok, and Llama are all trained on largely the same public internet data. When everyone trains on the same information, models inevitably converge. The real moat isn't the model itself. It's the proprietary data that sits behind it.

Source.

Companies that can train on exclusive datasets gain a huge advantage that competitors can't replicate. But the loop only works if you have the right people feeding it. Lawyers. Engineers. Doctors. PhDs and master's graduates, leaders from every discipline. People who actually do the work, who see exactly where models break down in production, who have the judgment to diagnose why, and who can feed that signal back into training.

Anyway, thanks for your service, Sidney. You're not even a year old and already the backbone of an AI analogy in a tech newsletter. You are set for great things. Now, let's talk about what training actually looks like in practice.

How to train a model

So what does it actually look like to train a model? Not in the abstract TED-talk, ‘we use reinforcement learning’ sense. What does a human being do all day?

At its core, the mechanics are simple. The model generates an output. A human evaluates it. The model learns. Repeat this a few million times, and you've got yourself a frontier AI. The thing is, "a human evaluates it" is doing an absurd amount of heavy lifting in that sentence. Because which human makes all the difference. Let’s dive into a mock example of what training looks like in the real world.

1/ A corporate attorney reviews an NDA, and the model says it is clean. It's anything but. There's a non-compete clause buried in paragraph 12 that's unenforceable in California but fully binding in Texas. The model doesn't understand jurisdiction-specific enforceability. It's never litigated anything. Why? Simple. Because it’s not a lawyer.

2/ A financial analyst estimates cost of capital in an emerging market. Two models answer. Both walk through debt ratings, sovereign spreads, WACC. One confuses book values with market values of equity. The mistake cascades through every number. A generalist nods along. An analyst who's priced deals in LATAM catches it right away.

Source: Scale AI.

3/ A mathematician reviews a proof; step by step, it looks airtight. Except that the model has confidently asserted that 3,821 is divisible by 53 and 72. It's not. 3,821 is prime. Duh! One actual mathematician described the phenomenon of AI as ‘very confident nonsense,’ you know the type.

4/ A researcher checks an AI-generated proposal. The citations look legitimate—correct journal names, plausible author names, realistic publication dates—except 69 out of 178 references don't have valid DOIs. Twenty-eight of them don't exist at all. The model invented papers. Confidently.

5/ A linguist evaluates a marketing campaign translated from English to Japanese. The grammar is perfect, but the humor has become humorless, the idioms are literal, and the emotional tone reads like a legal disclaimer. Studies show that literal AI translation can lose up to 47% of contextual meaning and more than half of emotional nuance. The words are right. The meaning is wrong.

A handful of other examples can be found below.

Two or three years ago, AI training really was the domain of basic crowd-sourced data labeling. Thousands of gig workers clicking ‘thumbs up’ or ‘thumbs down’ for a few dollars an hour. This still exists, and no shade to all those out there triple-checking that an orange is orange and a dog is a four-legged mammal, but the future has arrived, and it’s owned by the intellects.

The cat is out of the bag

Now that you have lived through the Idiot’s Guide to Training an LLM, I’d like to talk about the industry at large, and how it is an absolutely cashflow volcano hiding in plain sight. Recently, by chance, I stumbled upon Lenny’s tweet citing, “New fastest-growing company in history just dropped.” Obviously, when Lenny says something so outrageous, you take notice.

The company in question was Mercor, which began selling nearshore devs and later pivoted to post-training AI. The claim was that Mercor had grown its recurring revenue from $1M to $500M in 17 months. True breakneck speed, and such a pace that led to Benchmark’s Mitch Lasky bestowing them the title of “fastest growing company in history.” Mercor was founded by three young whippersnappers, Brendan Foody, Adarsh Hiremath, and Surya Midha, who began selling talent but soon, after going through the Thiel Fellowship, smartly pivoted to training AI.

Foody’s LinkedIn.

They have since raised $100M at a $2B valuation in February 2025, followed eight months later by a $10B valuation and a $350M Series C. They now have 30,000+ experts on their platform earning an average of $85 an hour.

What I found strange was that Foody seemed to be on a tear, running from podcast to podcast, screaming from the rooftops about their new business model. On top of that, only a month earlier, Garrett Lord of Handshake, the LinkedIn for new U.S. grads, was doing the same thing. After his decade-long startup pivoted part of its operations to training, the team accumulated tens of millions of dollars in revenue in a matter of months. I don’t know about you, but I consider this to be firmly letting the cat out of the bag. If I had stumbled upon an industry that was growing this fast and happened to be leading it, you would have to pry that information from my cold, dead hands.

With immediate fallout from Meta’s June 2025 acquisition of Scale AI—OpenAI, and Google both stopped working with Scale after the deal was announced—a vacuum has opened up, allowing upstarts from a number of industries to fill the void. Turing, Andela, and my company, Athyna, have all entered the arena.

The connective tissue between these companies, with very different origins, was one crystal clear insight: the most valuable commodity in AI isn't compute, code, or even data. It's trained humans who can train machines. The training industry hasn't just seen changes over the last 18 months. It’s been fractured, reshuffled, and grown again, to a size and scale much bigger than before.

The talent war nobody's talking about

The question of AI in 2026 is: Where do you find 30,000 PhDs who want to spend their Tuesdays evaluating whether an AI model correctly interpreted a chest X-ray? Every frontier lab (Anthropic, OpenAI, Google DeepMind, Meta, xAI) has an insatiable demand for expert human feedback, at scale. Not click-farm scale. Expert scale.

They need mathematicians verifying proofs, lawyers spotting buried clauses, engineers evaluating code, and 10,000 other use cases across every domain an LLM touches. If your second cousin has a PhD in molecular bio-something-or-other, tell them to call their wife and tell her to ‘break out the red panties, because babay we made it.’

_{*If you don’t know that last reference, it was a poorly executed, somewhat obscure Conor McGregor reference that only total MMA nerds would know. Also, I do not condone who Conor has become, but I reserve the right to use his best lines from now until forever, because let's be honest, they are pretty great.}

The fact of the matter is that the supply side is very thin. There are roughly 4.5 million PhD holders in the United States. A fraction of them are in the fields that matter most for AI training (computer science, mathematics, medicine, law, hard sciences). An even smaller fraction is willing to do contract evaluation work alongside their day jobs or academic positions. The bottleneck isn't money; these roles pay $85 to $125 an hour. The bottleneck is finding, vetting, and deploying the right people at speed. This is where geography is becoming a weapon.

Brazil, known for many cultural exports, including football and açaí, also has one of the largest concentrations of PhD holders in the Western Hemisphere. Argentina, led by the new age Austin Powers with a chainsaw, Javier Milei, produces world-class mathematicians and computer scientists, and always has. Chile, Mexico, and Colombia all sit on deep pools of advanced-degree talent that Silicon Valley has historically overlooked. And the economics are hard to ignore: a PhD researcher in São Paulo or Buenos Aires can be engaged at 40-60% less than their counterpart in San Francisco or London, while still earning a globally competitive wage by local standards.

Deel’s recent Global Hiring Report 2026, actually showed huge growth in openings for AI trainers, growing 283% cross-border last year. It’s one of the fastest-growing roles in tech, and one that is showing over 40% of talent being paid to come from outside the U.S., in countries like India, the Philippines, and Canada.

Source: Deel. Source: Deel.

Source: Deel.

Why we launched Athyna Intelligence

In the spirit of open-sourcing in this newsletter, I like to break the fourth wall from time to time and, in this case, talk about our decision at Athyna to throw ourselves headfirst into the post-training space. The TL;DR is that we've spent the last several years building one of the largest curated talent networks in Latin America. Over 150,000 vetted professionals across engineering, design, marketing, ops, you name it. We've placed talent at more than 1,000 companies, from scrappy seed-stage startups to Fortune 500.

So, you can understand that as soon as my GM and I stumbled upon this opportunity—kudos to Tino for bringing it to me—we started devouring any information we had on it.

This led very swiftly to us coming to the realization that this was: a) within our hitting zone and b) one of the biggest opportunities we could attack at this stage of the business. So, we assembled our version of the Athyna Avengers: myself, Tino, our GM, perennial superstar Josie, now lead of the AI project, and around 10-15 others to tackle things head-on.

What is it? Well, alongside Athyna Talent, our original tech hiring product, we launched Athyna Intelligence, a dedicated vertical within the company focused exclusively on AI training and evaluation. Data generation, annotation, model scoring, classification, reasoning benchmarks, prompt testing; the full stack of what AI labs and application companies need to make their models better. The difference is who is doing the work. Our network includes researchers and advanced graduates with backgrounds in computer science, mathematics, engineering, and NLP. PhDs from some of the best universities in Brazil, Argentina, Chile, and Mexico.

The crazy thing is that we started getting interest from the biggest names in tech in the first month after launch. I am not sure if I am allowed to comment on these conversations, but let’s just say we are currently recruiting for and in conversations with the two biggest ride-hailing apps in the world, a certain search behemoth, a tool to replace Photoshop, and loads more.

Train your models.

With our existing Talent product, we are successful in any meaningful sense of the word: profitable, growing quite nicely, strong culture. But even so, we don’t get inbound and easy-to-open doors from the biggest of Big Tech. I put this down to two things.

Firstly, the talent depth is unmatched. We've spent years building a curated network of researchers, engineers, and advanced-degree holders across Latin America — people who are genuinely world-class at what they do. Time zones are aligned with North America. Culturally aligned with Western business norms. And critically, fast. The fact that the economics also happen to work in the buyer's favor is a bonus, not the pitch. The second is that there is an insatiable demand for this product. In the past, you'd often hear about the war for talent. Today, it is a war for training.

Pssst…also

We’re looking to connect with the heavy hitters in the space, and we’re willing to pay in equity to make it happen. If you can bridge the gap between us and our Dream 100 list—think the big players at OpenAI or Midjourney—we’re offering $25k in equity per successful intro.

The rewards don’t stop there: we’re adding a $50k equity kicker for every client that signs on to our Intelligence product through your referrals. If your Rolodex is full of AI experts and founders, hit me up here. Let's build something big together.

Looking ahead

This industry is going to get much bigger before it gets smaller. Every new model, every new capability, every new vertical application requires more training data, more expert feedback, more human-in-the-loop evaluation. And as models get more capable, the bar for what constitutes 'good' training data goes up.

The companies that win won't be the ones solving the compute problem; they'll be the ones solving the talent problem. Who has access to the deepest pool of domain experts, and who can deploy them fastest? Some smart people think AI will eventually train itself, and maybe they're right. But until then, this gold rush will continue. Only this time, the picks and shovels are people.

Extra reading / learning

• What is Vibe Marketing? The Complete Guide - October, 2025

• If You Ain’t AI First, You’re Last - November, 2025

• Battle Royale: ChatGPT vs Claude - February, 2025

And that's it! You can follow me on Twitter and LinkedIn, and also don’t forget to check out Athyna while you’re at it.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Vanta*—the security and compliance platform companies rely on to stay audit-ready without losing their sanity.

beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 4,512 new legends who joined since our last edition! You are now part of a 310,727 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

👏🏻 The Invisible Layer Separating Good AI From Great AI. An interview with Tyler Phillips, AI Product Lead at Apollo.io.
🚴 Fundraising Fatigue, Hypergrowth & Selling Glovo. An interview with Oscar Pierre, Co-Founder & CEO at Glovo.
❤️ How Athyna Makes Remote, Work. Tech, meetings, culture & comms. How to do it and maintain 90% engagement.

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• Applied ML at scale

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• 40–60% cost savings

Part of our vetted LATAM PhD and Masters network, working in U.S.-aligned time zones.

_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

This week, we welcomed one of the most talented people I’ve ever worked with back into the fold. Sort of anyway. My buddy Lucas Saud, who led sales at Athyna for years alongside Tino, our GM, has now returned as the founding sales manager at Open Source CEO. It’s a real prodigal-son returning from the hero’s journey moment.

It’s amazing that our best keep coming back to Athyna, and in this case, Open Source CEO, but Lucas’s hire is an incredible one for me, because it frees me up to work more creatively and strategically. As someone who has worked 60-70 hours for a decade, I am at a point where I am no longer the engine room. This means I can spend more time taking Ziggy down the beach, as seen in the image above. Oh, and by the way, today’s piece is with a company I am personally using, and loving, Ultrapseaking. Check them out if you are looking to up your leadership game.

INTERVIEW 🎙️

Tristan de Montebello & Michael Gendler, Co-Founders of Ultraspeaking

Tristan de Montebello and Michael Gendler are the co-founders of Ultraspeaking, a communication school built on a counterintuitive idea: most speaking advice fails because it focuses on surface-level fixes instead of the real problem: what happens inside your head when the stakes go up. Tristan's story is the company's origin story. In 2017, he went from avoiding public speaking entirely to competing at the World Championship of Public Speaking, becoming the fastest competitor in history to reach the finals in just seven months. His coach through that journey was Michael, a UCLA computer science graduate who had made an unlikely leap from software engineer at companies like Symantec and Hulu to one of the world's leading public speaking coaches.

Together, they have coached Fortune 500 executives, entrepreneurs, and creators with 1M+ subscribers to speak with confidence in the moments that matter most to them. Their method is like nothing I've seen. Instead of memorizing frameworks or counting your 'ums,' they focus on rewiring how you think and perform under pressure, using fun, high-energy games that simulate high-stakes moments in a safe environment where you practice and get real-time feedback from peers and coaches. The results have earned them a very loyal following of founders and leaders, including me, Lenny Rachitsky, Eric Partaker, Chris Donnelly, Tiago Forte, Jesse Itzler, and Greg Isenberg.

Why are you guys building Ultraspeaking?

Tristan: For me, it's my longest and most personal project. Ultraspeaking was born of my own journey to figure out the root cause of what was holding me back from communicating effectively. It was the anxiety and overthinking. Once we solved that, while still allowing me to feel like myself, my quality of life improved so dramatically that I discovered a deep passion for this path. I hope that the entire world experiences what I've experienced. It's as simple as that.

Michael: Speaking is a meta skill, and unlike piano or some really narrow skill, a meta skill feeds into so many other aspects of your life and elevates them. Public speaking is not really the skill we are passionate about; we're passionate about the skill of feeling at ease in every scenario. The ability to express yourself effectively everywhere: in the presentation, in the meeting, in the difficult conversation, on stage, off stage, introvert, extrovert, it doesn't matter.

That's the meta skill that makes life so much richer, because most people are carrying around a lot of self-consciousness, a lot of anxiety, a lot of imposter syndrome. That's a drag on your life, a weight that is just making life more miserable than it has to be.

Lifting that weight off and letting it go means you walk around feeling lighter everywhere you go.

The compounding effect of that is not only that you feel better, but that you perform better, too. Speaking is a huge part of our professional success and our relationships. Improving your speaking skills compounds exponentially on how the rest of your life goes. So if there's any skill to invest in, speaking is a good one, because we spend most of our lives doing it.

Are there mental health benefits to actually working on this as a skill?

Tristan: When you don't trust your ability to get what's in your head out into the world, and instead you're carrying this belief that you're going to say the wrong thing, that takes a real toll on your nervous system and your psyche. The way I like to think about it is that most people are navigating the world like an obstacle course. There are areas where you feel comfortable, and you're fine there. But then there are all these other situations where your nervous system gets jacked up, and you lose confidence and sleep over them.

For example, more commonly than you’d think, I’ll coach someone who thinks getting up onstage in front of 1000 is not a big deal, but they are terrified of a board member asking them a question they don't know the answer. So they over-prepare for those situations and overthink them, or they find a way to avoid them entirely. That takes a toll on their mental health.

One day, in the early years of my being an entrepreneur, there was an influencer who was really interested in our product. He invited me to an event. I didn't really know him beyond a few interactions, but he was a big deal in my mind. I remember showing up, and he was standing right in the entryway. It was on a boat on the Seine in Paris. There was no way to walk in without passing him. I knew he knew what I looked like, and I immediately recognized him.

I got so scared because I didn't know what to say or how to talk to him. And this all happens in seconds. I'm walking towards him, I pull out my phone pretending I'm getting an important call and start talking: 'No, really? Is that really happening? Oh my goodness.' I stood near him for about ten minutes on this fake call, debating what to do. And then I left the event without going in. I think a lot of people live in a world where some version of that is true.

What are some common misconceptions about public speaking?

Michael: A really common one is around clarity. What's clear to you may not be what's clear to others. I see frustration around that all the time. People think, "I explained that so well.” Or “We talked about this.” Or “Why is this other person suddenly coming back to me, not doing what I asked them to do?" Well, you thought it was clear to you, but was it clear to the other person?

Used by leaders at the companies above.

It’s surprising. When we study communication clarity, we realize that most leaders and executives still struggle with speaking at a high level. They default towards complexity over simplicity. They feel they need to go into detail to be clear. The most common reality is that they are not even clear on what the most important thing they want to share is.

Clarity is about simplicity. It's about recognizing the one thing you want your audience to remember. If you don't have clarity for yourself, your team will never find it in the details.

What are the things that differentiate great leaders from not-so-great ones?

Tristan: Great leaders listen. I think it's underappreciated how much listening is a part of excelling at effective communication. A classic situation is when everyone is going around the room introducing themselves, and you're the last to go. Instead of listening to who everybody is, you're rehearsing what you're going to say because you're afraid that when your turn comes, you won't know what to say. The only way you can truly listen is if you trust yourself enough to know that in the moment, the right words will come.

Michael: A surface-level public speaking coach might say great leaders pause, but that's just the symptom they're observing. The pause comes from a place of unhurriedness. There's no rush. Unhurriedness also allows a leader to speak with conviction, because when they say something important, they let it breathe. They pause and let the words sink in.

Sometimes I see leaders say brilliant things, and the moment they land their point, they're already on to the next words. They're rushing because they fear that if they take up too much space, people will get bored.

Unhurriedness really comes from a place of believing that you deserve to take up space. It's worthwhile to pause. The audience will appreciate the time you give them to digest the importance of what you're saying.

That level of confidence to pause, to take your time, is a hard skill to train out of the box. It lies on the level of your belief systems, your sense of worthiness, and your sense of belonging.

It’s why another common misconception about speaking is that it's just a tactical skill set, when it's not. It's a tactical mindset: a set of beliefs and mental models that unlock your speaking skills.

What are the most common areas for improvement for a leader?

Tristan: The first thing I look at is where this person is on the spectrum of speaking anxiety. Are you the type of person who tends to avoid high-stakes speaking or looks forward to it? That's the foundation of it all. The types of people who wouldn’t walk up to the influencer because they’re scared can learn as many frameworks, tips, and techniques as they can fit into their brains, but nothing will work. They are also the types of leaders who hold back what they're actually thinking in a group.

For the people in the middle of the spectrum, and most high-performing leaders fit here, their challenge still stems from self-doubt, but it just shows up differently. They’re rambling, or they’re speaking really fast, or they’re monotone. They tend to speak a lot.

Michael: We were hired by a CEO to work with his entire leadership team. It was really interesting. Half of the people had the problem of being talkers: rambling, circling around the point, being too verbose, or not getting to the point quickly enough. The other half had the opposite problem, as Tristan brought up. They’re brilliant, but they weren't speaking up. They were hesitating, not sharing what was actually on their mind unless prompted. They needed more confidence.

What I find most interesting is that the CEO was an exceptional communicator and is someone who looks forward to speaking in all professional scenarios. But the moment the camera came on, he’d become robotic and just couldn't feel natural. We’re seeing a big trend of CEOs coming to us for help with this as they build their personal brands to market their company. Learning to be conversational, at ease, and to express yourself well, no matter what scenario you are in, is probably that final meta skill that we found leads people to enjoy speaking. That comes down to having enough reps and the right mindset.

💡 Note: I am currently using Ultrapseaking myself, and I absolutely love it. Big recommend if you are looking to sharpen your leadership!

What methods do you use with broad groups, and how do they work?

Tristan: I think it's important to understand how we think about communication training and how different it is from what most people have in their minds. If you look at the lay of the land of what communication training looks like, it is very much framework-oriented: use this framework, this tip, this structure, and these rules, without looking at where you are. What we've found is that that is not the most effective approach, and perhaps just as importantly, it's not the approach that will activate the lever of the meta skill where it starts impacting everything else in your life. We train by rewiring your brain and relationship to speaking. One of my favorite tools for that is a game we created called ‘Conductor.’

In the game, I control your energy, vocal variety, and intensity as you speak. I give you a random speech title and ask you to change your energy levels—sometimes with big jumps and contrasts, from very low to very high energy, or from low intensity to high intensity —while also exploring different emotions: excitement, frustration, introspection, and everything in between. The reason this exercise is so effective is that you discover everything you need to let go of control. It's a tool that acts as a mirror, showing all the areas in which you tend to have low trust in yourself, the areas that feel very much unknown to you.

Ultraspeaking coach, training using the game ‘Conductor.’

In the game, the Conductor will say, "Raise your energy to an eight, nine, or ten out of 10 intensity," and you can't do it; there's no way you're going to have conviction in the meeting. If the conductor says, "Give me a one, two, or three out of 10. Really slow it down," and the person keeps speaking quite fast and won't pause, there's no way you're going to have executive presence or gravitas in the meeting.

So, going through the Conductor exercise helps surface the skill sets required for being an effective, well-rounded communicator.

Michael: I want to share an effective method for presentations. It's called the ‘Five Minute Presentation’ game, and we play it in one of our cohorts. You have five minutes to create a presentation on a topic you just heard about, complete with slides, and then you have to present it. That's insane time pressure; having to think, design, and present a slide deck in five minutes is really tough, but it builds the right fundamentals.

First, it forces you to figure out what's the one message that matters most. Many people don't even think about that when they have two days or two weeks to prepare a presentation. Second, it reminds you to set an intention, because one of the biggest levers you have when presenting is deciding how you want to make people feel. ‘Am I going to use humor? Is my point here to entertain, to inform, to inspire?’ Most people don't set that consciously, so they're not pre-planning or trying to optimize for an audience reaction.

Source.

‘The champ is here.’

Third, it builds the best habit of not overcomplicating your slides. When you're playing the ‘Five Minute Presentation’ game, you can really only do one image and one headline per slide, and as a result, you build what we call the ‘campfire effect’: the effect where your slides are there to create ambiance and support your story, not to dominate and take away from the spotlight.

This game is a really fun way to get lots of reps in within a single hour. It helps people overcome perfectionism when it comes to presentations and build the highest-leverage habits so they can ingrain the skills that matter most when presenting.

What does real executive presence look like on a stage?

Michael: Most people think that executive presence looks like a sort of posturing or confidence, so they try to emulate the physicality of it. Maybe you stand with both feet solid, maybe you have your shoulders back, maybe you punctuate your words with hand gestures, maybe you speak with conviction. But I don't think that's what executive presence really means, because when I study executives—whether on a stage or in a meeting—presence, to me, means complete ease. Complete ease and certainty in oneself.

That could look like a commanding presence if that's what ease feels like to you. But to a lot of people, ease feels like being able to sit back a little in a meeting, maybe even slouch a little, because you're comfortable. You have no self-consciousness about what other people are thinking of you.

Think about the CEO; they're probably oftentimes the most relaxed person in the room, because everybody reports to them. Everybody else is on edge, but the CEO is relaxed. So how does the CEO behave? In a relaxed way. They'll crack jokes, they'll use humor, they'll lean back. To me, that is a more modern-day version of executive presence. If you try to fake executive presence, you might sit straight or stand up with great posture, but you'll be performative. You'll be trying to act like an executive, but that's not the goal. The goal is to feel like an executive. And what do executives really feel once they have the title and the experience? They feel at ease. They're relaxed.

I think that's what you want to see on stage: someone who is conversational, someone who has humor, somebody who's not afraid to laugh at themselves, and somebody who, when the time is right, will drive their point home with conviction, in a way that's unhurried, because ultimately they believe that they deserve to be there and that what they have to say really matters.

What's an example of someone making a transformation working with you?

Tristan: I have a person who comes to mind, a very senior executive of an engineering team at a big tech company. He is a remarkable expert in his field, truly top 0.1%. Yet he was carrying a debilitating anxiety around speaking that no one was aware of. Not his family members, not his girlfriend, nobody on his team. Nobody. He had gotten really good at avoiding speaking in groups. He would give a presentation to a member of his team to present or use 1:1s to communicate.

What's interesting about this person's story is that, when he joined Ultraspeaking, he felt, after just a class or two, that it was too hard to overcome and that his situation was too unique to fix. He quit. And three months later, he came back, and this time he said, "I don't care what it takes, I'm doing it. Enough is enough." He became one of our star students. He took all of our courses multiple times and trained every single day. A few things happened. *Note: Riverside AI-suggested this image for us; why so pensive?

One, he discovered he was definitely not alone. There are, in fact, an insane number of people who experienced the exact same thing, and he had found a community where all kinds of very powerful, interesting, smart people were working on the exact same problem.

That transformed how he felt about himself, especially at work. What makes this story stand out for me the most is that I had a conversation with him after he visited his family for a few weeks. He told me, "I had deeper conversations with my siblings than I have ever had in my entire life, and I attribute 100% of this to the transformation I went through in Ultraspeaking."

Michael: The person that keeps coming to mind is Tristan. He's my favorite success story. Here's a guy who was just an average person with no speaking training, who would actually turn bright red every time he spoke in groups. It was a friend of his who said, "I think if you're going to spend time developing a skill, do a meta skill." That's actually how we even learned about the phrase meta skill.

So Tristan decided to study public speaking since it was a meta skill where he was truly starting at zero. And because he's a unique learner, who dedicated hundreds of hours and intensity, his first accomplishment was reaching the finals of the World Championships of Public Speaking in just seven months, which is insane. That doesn't just happen.

A happy bunch of confident speakers.

The reason I love this example is that, first, it shows that all of this is entirely learnable. Everything in the world of speaking, leadership, and communications is learnable, but you have to find the right way to learn. It has to be motivating and fun so that you stick with it, and you need good mentors, coaches, advisors, and a community surrounding you on the journey.

Second, it compounds exponentially and changes your life. He never expected to win the semi-finals. He never expected to start teaching and coaching speaking skills. He never expected to be the CEO of a communication company. For myself, when I started working on my speaking skills, I just did it to overcome anxiety. I didn't expect that a year in I would be able to negotiate 2x my salary. There are so many implications: a better career, a better salary, new opportunities, starting your own business, and recording videos on YouTube.

Your whole life can change when you start working on your speaking skills, and you can't really predict how. But the momentum you build and the skills you unlock will open up a whole new world. Tristan is an example of the extreme of what's possible, but I've seen a lot of extremes, and that's the beauty of this skill. It really changes your life.

Extra reading / learning

• Why most public speaking advice is wrong - October, 2024

• How to speak clearly on-the-fly - March, 2024

• 5 Powerful Habits To Build Unshakeable Confidence - February, 2024

And that’s it! You can follow Tristan and Michael on LinkedIn to keep up with them. Or check out Ultraspeaking at their website to learn more.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting BILL—only one platform for managing bills, spending, payments, and approvals, with automated workflows that cut down manual work.

beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 5,511 new legends who joined since our last edition! You are now part of a 306,215 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

🚴 Fundraising Fatigue, Hypergrowth & Selling Glovo. An interview with Oscar Pierre, Co-Founder & CEO at Glovo.
❤️ How Athyna Makes Remote, Work. Tech, meetings, culture & comms. How to do it and maintain 90% engagement.
🏄🏻‍♂️ Eight Very Cool Marketing Things. Insights I've found from around the web in the last weeks.

PARTNERS 💫

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HOUSEKEEPING 📨

The internet is unbeatable. This meme, for example, is just too good not to share. And yes, it’s political, and no, I don’t like Trump, but the point here is that someone found this cultural reference, right as we are neck deep in Dune lore, of an evil green pedophile, dragging everyone into war. You don’t need Trump Denangement Syndrome to appreciate the wonders of the Internet in this example.

Source.

As for everything else lately, my life could be summarized like so: work, train, Claude Cowork, train, workout, eat san choy bao, Project Hail Mary, Claude Worok, work, train, Claude Cowork. Going to break up the monotony by heading to a stand-up show tonight, and if we don’t get back, I might play around with some Claude Cowork before bed. Enjoy today’s piece!

INTERVIEW 🎙️

Tyler Phillips, AI Product Lead at Apollo.io

Tyler Phillips is a seasoned product leader, currently the Director of Product & Head of AI at Apollo.io, a fast-growing AI-powered go-to-market and sales engagement platform. In his role, he leads development of Apollo’s AI Sales Assistant and broader AI platform initiatives designed to help businesses of all sizes discover, engage, and convert prospects more effectively. His work centers on building scalable AI solutions: he led Apollo AI product strategy and a 40+ person R&D organization, built the AI Assistant from zero to 21k WAU, and launched a research agent that reached 47M enrichments/month, driving $XM in add-on ARR, and grew Apollo AI's combined product suite to 50k WAU in 2024.

Tyler.

Before focusing on AI at Apollo, Tyler built a broad product career spanning B2B technology and growth roles, where he emphasized problem-solving, product quality, and user-centered design. At Apollo, he has been featured in industry conversations about what it really takes to deliver high-quality AI products in the go-to-market space, highlighting the importance of systematic evaluations and domain expertise in shaping successful AI outcomes.

What problem are you trying to solve with Apollo, and why?

Apollo is a go-to-market platform for SMBs and enterprises. The main problem we’re trying to solve is helping you find the right person at the right company at the right time, reach out to them, and book meetings. It sounds like an easy problem to solve, but it’s actually very difficult. The second problem we focus on is helping you convert inbound traffic from your website into customers. And third, once you’ve booked a meeting, how do you prepare for it? How do you execute the call effectively and eventually close the deal? So, we’re really thinking end-to-end across the entire sales funnel.

As for why this problem, if you can make someone $10, you can charge them $1. It’s a pretty self-evident problem to solve. I also find it fascinating because it’s constantly changing. What worked last year won’t work this year. You have to continually adapt your go-to-market strategy to find the edge and generate outsized returns. That’s what makes it interesting to me.

What’s hardest when going from early AI prototypes to a tool customers love?

The hardest part is getting to something that’s truly usable. It’s much easier to ship an initial version that people try once and then drop. The real challenge is building something reliable. For example, when we launched our Apollo AI assistant in Closed beta last June, the success rate was around 26%. That meant roughly three out of four people who used it didn’t get the outcome they wanted or didn’t have the right action taken. It’s very easy to stand up an initial system using base-level LLMs and some basic agent implementation. But getting to 80–90% quality, where the conversation or agent consistently takes the correct action, is extremely difficult.

Source: Apollo.io.

The reason why it’s so hard is that you don’t actually know what users are going to ask. You can guess, and that’s part of product management, but there are always edge cases you didn’t predict. You need to build a much more sophisticated system and fine-tune it to the user’s needs. For vertical applications in particular, depth matters. You have to cover as many edge cases as possible, and that just takes time. We’ve worked on it for over a year, and it’s still challenging to reach even a 90% success rate. But that’s where AI products are won or lost. Quality is everything.

What does your day-to-day look like leading AI?

My day-to-day is generally split across three areas. First is strategy. I’m constantly looking at our objectives, things like AI credit consumption or driving AI-assisted actions on the platform, and asking what bets we should be making to achieve our goals and help users succeed. That includes deciding whether to invest on the UX side, the quality side, or elsewhere, and then aligning the team around the right priorities.

Source.

Second is execution. I’m both an individual contributor, product manager, and a product leader, so I’m still very hands-on. I write PRDs, run evaluations, and review outputs. I spend a lot of time every week in spreadsheets going through AI outputs and running evals. Third is staying close to the customer. I meet with customers, review chat logs, and try to deeply understand what they need and how we’re positioning the product to serve them. I also spend some time hiring. That’s generally how I divide my time.

Where is AI most effective in augmenting sales workflows, and where does it fall short?

I think a year ago, many people assumed AI would take over messaging. Now almost every seller uses AI for messaging, but it’s proving to be less effective than expected because it’s easy to tell when something is AI-generated. With tools like Gmail’s AI previews, it’s almost like AI reading AI, and AI is pretty good at detecting when the other side is also AI. It becomes a bit of a feedback loop.

Where AI has been most effective is in targeting. It’s very strong at researching accounts and contacts, at least for a first pass, by combining data from your CRM, your product, and the web.

For example, we worked with a translation company that used to manually visit websites to check for translation gaps between languages like Portuguese and English. With AI, they can now identify those gaps instantly. That makes qualification and research much faster and more scalable.

Source: Apollo.io.

The second area that’s starting to emerge is analyzing go-to-market data to improve your understanding of your ideal customer profile. It’s about using the feedback loop—who you message, who responds, who books meetings—and feeding that information back into either a machine learning model or an LLM. With more data available, you can organize it and use it to refine your targeting and messaging strategy. That’s the next big vector we’re seeing.

Will AI messaging eventually be indistinguishable from human?

I think it’s conceivable. I don’t know if we’re that far away, but if you’re just using a one-shot prompt in something like ChatGPT or Claude, it’ll be obvious. As systems become more advanced, they can truly understand your tone and voice, and capture rep feedback as they manually edit emails; I think they’ll get much better. Once you start building a system that learns from edits and adapts over time, the outputs can improve significantly.

The main blocker right now is having really strong context and tight alignment with your tone and voice. If those pieces are in place, I do think it’s possible. Some companies are already doing a good job with this. But for now, it’s still a challenge.

How do you decide what’s automated with AI vs. human-driven?

I’m a big believer in automating transactional, lower-level tasks. AI is well-suited for things like creating workflows to automate manual processes that users have already seen success with, building lookalike campaigns based on what’s worked before, or handling research and account updates. These are more menial tasks where a human isn’t uniquely positioned to add value.

Source: Apollo.

Where humans are still essential is in the actual human component: real conversations and understanding nuance on the other side. AI isn’t great at catching subtle signals in live interactions. Messaging, cold calling, and real-time communication still benefit from human judgment and review. I also think creativity should remain human-driven. Go-to-market today is about standing out. The best marketing ideas don’t typically come from an LLM. You’re not going to ask one for breakthrough ideas and expect something truly original. Creative thinking is still in high demand, and that’s where humans have the edge.

How are you personally using AI in your own workflow?

I use different LLMs for different use cases. I use Perplexity for web research and searching; I don’t really use Google anymore. For deeper work, I use Claude as more of a coworker, especially its Projects feature. I use it for writing PRDs, shaping strategies, drafting OKRs, and things that require structured thinking. I find it particularly strong in writing.

Source.

Tyler x OpenClaw.

I’ve started experimenting with tools like Cursor and Claude Code. I use Claude Code to go from zero to PRD and Prototype, as well as automate mundane tasks like weekly updates. I use Cursor to connect to Apollo’s codebase and ship very basic PRs that my engineers review. I use OpenAI more for personal use cases, like cooking. At work, I use Glean to extract and summarize information from JIRA tickets, Notion, Slack, and other systems. I also use Slack AI to some extent. Overall, I tend to assign one core use case to each model based on what it does best, and that’s how I structure my workflow.

How do you think about leadership and culture?

A few things matter to me. First, create a culture of ownership. It’s easier said than done, but we set aggressive goals as a company and then assign one person to fully own each goal. That person operates almost like a GM for their area. They’re responsible for driving it forward, succeeding if possible, and if not, learning why we failed and how to improve. When people feel like owners instead of just executors, they tend to do exceptional work.

Second is incentives. I believe in a performance-based culture. If you perform well, you should be rewarded. We’re not a family, we’re more like a sports team, similar to the Netflix philosophy. Of course, we treat people well, but performance matters, and incentives should reflect that.

Finally, it’s about genuinely loving the customer. It’s easy for you to say you’re customer-first, but it has to be lived. Instead of just reading about how to build a campaign, go into Apollo and learn how to build one yourself. Instead of just shipping a feature, work directly with customers to get them using it and gather feedback.

That mindset should apply to everyone. When people are motivated by the same goals and rewarded accordingly, it creates a culture where they’re excited about what they’re building.

Is there any question about building product that you wish more people would ask?

One question I always like to ask is: how do you actually run evaluations? People focus too much on the product itself, but the real key to success lies in how you evaluate and improve it. The process you use to run evals and continuously raise quality is what ultimately determines whether you build a great AI product. In many ways, quality is the product.

The best use Apollo.

Another important question is: how does context work in your product today? Context is a major area that has been underserved so far. We made a big bet last year to build in more context, and I still don’t think we’ve done enough. The companies thinking furthest ahead about context are going to be the ones that win.

Can you explain the relevance of context in more detail?

We think about context from a few different angles. First is business context. That comes from your source of truth: your CRM, website, internal documents, and other systems that are constantly updated. That gives the AI an understanding of your company and what’s happening inside it. Second is user context, which is more like memory. If you’re interacting with an assistant, how does it learn who you are, what you’re trying to accomplish, and how you use the product based on your behavior?

Third is context from activity outside of Apollo. For example, we have a browser extension that lets us understand how users interact with prospects across email and other networks. That helps us see what they’re actually trying to achieve, not just what they’re doing inside Apollo. Fourth is skills-based context. Claude has a concept of skills, specific actions an LLM can take. In our case, we have domain expertise in go-to-market on our team, so we want to translate that into skills our AI can use. That means embedding go-to-market expertise directly into the system.

Finally, there’s what we think of as ‘a context graph’. This goes beyond just capturing activity. It looks at what led to a successful outcome, like a booked meeting. Which companies did you target? Which prospects? What emails did you send? What replies did you get? From there, you can build a decision tree that guides the AI toward sequences that have historically worked and suggests improvements, like refining the target list or adjusting messaging. Bringing all of that together is our goal for building a strong context layer at Apollo. We’re well-positioned to do it because we already have access to this data through our product suite. Now it’s about executing on it.

How do you get the best out of yourself personally and professionally?

I began writing weekly reviews while running my own company before Apollo. Every week, I look at the different areas of my life—relationships, career, finances, health, fitness—and revisit what I want to achieve this year and how I’m progressing toward each goal. I think having a balanced life makes you a better professional.

Sharing the secret sauce.

If you only focus on work, you miss the bigger picture. Paying attention to whether you’re healthy, eating well, and feeling connected to a community matters. Being well-rounded helps you show up better at work. I also like to take on challenges outside of work. For example, right now I’m training for the Murph challenge: 100 pull-ups, 200 push-ups, 300 squats, with a mile run before and after. Doing difficult things outside of work builds discipline and resilience. That carries over into how you operate professionally.

Extra reading / learning

• The Secrets To Being A Great AI PM: Evals, Quality & More - March, 2025

• What To Expect From Apollo Next with Tyler Phillips - February 2025

• The Complicated Reality of AI Implementation in Engineering Teams - June, 2025

And that’s it! You can follow Tyler on LinkedIn or check out Apollo.io on their website to keep up with what they’re building!

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Metal*—a smarter way to search for investors, match by fit, and skip the endless cold-outreach guesswork.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

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🏄🏻‍♂️ Eight Very Cool Marketing Things. Insights I've found from around the web in the last weeks.
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HOUSEKEEPING 📨

Fun fact: This newsletter was inspired by an interview series called How Do You CEO? by a buddy of mine, then-Startmate CEO Michael Batko. I got to know Batko through my investing and mentoring at Startmate, the Southern Hemisphere’s best startup accelerator—YC del Sur, some call it—and after nearly a decade at the helm, he’s now out on his own. If you have startup problems, he can probably solve them.

See more here.

Under batko.ai, he is helping founders raise, sell, and just generally be better at whatever it is they want to be better at. If you are looking for someone to help you. I highly recommend. Now, let’s jump into today’s post!

INTERVIEW 🎙️

Oscar Pierre, Co-Founder & CEO at Glovo

Oscar Pierre is the Co-Founder and CEO of Glovo, one of Europe's most successful on-demand tech platforms. Coming from an entrepreneurial family with his father running a digital consultancy and his grandfather operating a food distribution company, Pierre studied aerospace engineering at the Universitat Politècnica de Catalunya before transferring to the Georgia Institute of Technology in the United States.

Oscar.

Pierre founded Glovo in 2014, inspired by platforms like Postmates during his studies at Georgia Tech, and met his co-founder, Sacha Michaud, in 2015. Under his leadership, Glovo has grown from humble beginnings—holding early meetings at McDonald's—to becoming a multi-billion-dollar unicorn operating in over 1,800 cities across 22+ countries in Europe, Central Asia, and Africa. In 2022, Pierre successfully navigated Glovo's acquisition by Berlin-based Delivery Hero for €2.3 billion, in which Delivery Hero acquired a 94% majority stake while allowing Pierre and his team to continue operating independently. Despite the acquisition, Pierre remains actively involved as CEO.

What are you building at Glovo?

I was initially inspired more than 10 years ago by the digital platform ecosystem in Atlanta, US, and its impact on the student base there. We identified a new opportunity: rather than transporting people, we could help them with their daily errands.

Growing up, my mum was always running errands for me, my brother, or my dad. I thought we could save people a lot of time by building a digital service that allows you to send keys across town or have milk delivered to your home. Time is our most valuable resource. Our founding vision was to help people make the most of their day by making things accessible through tech and delivery. Soon, however, people began using Glovo to order food from McDonald's and other restaurants, which indicated that the initial focus should be on food and making it possible to order and receive it from home. There were apps in place, but they only connected restaurants to customers; they didn't provide the rider intermediation service.

What was the most difficult when going from zero to one?

The hardest part was building a marketplace from scratch. Glovo wasn’t just a two-sided marketplace, but a three-sided one, which made the chicken-and-egg problem even harder. It was very difficult to convince restaurants and riders to join when there were zero orders. We had to be creative. We gave riders credit cards so they could buy from any store, which allowed us to operate as a two-sided marketplace at first.

Fundraising was the other major challenge. The business required very large rounds, and raising that capital from Barcelona was tough. There was a strong bias that winners in this space would come from the US or the UK, and that scepticism made fundraising significantly harder in the early years. Additionally, each time we expanded to a new territory, we started from zero again. You need to be the number one or two choice in a country to be able to really grow and become profitable, so the first-mover advantage in each case is super vital.

At what point did you crack the chicken-and-egg problem?

There were a few moments when it became clear that the model was working. The first was when we realized that if you upload enough high-quality content into an app that enables delivery, people will order. We listed big chains and top restaurants, and customers were willing to pay high delivery fees and repeat the experience. Once we had around 100 customers who genuinely loved the product, we knew there was something there.

The second moment was signing our first high-quality restaurant partner, a sushi restaurant in Barcelona. For the first time, a restaurant agreed to pay a meaningful commission, helping validate the model's economics.

The third and biggest moment was signing a commercial agreement with McDonald’s in Spain. We were the first to break their exclusivity with Uber Eats. That deal didn’t just prove the model worked—it showed that we had earned the right to compete, even as a young and underfunded team.

Inbound interest started once we proved that customers were actually ordering. After we launched with a large amount of content and saw people paying delivery fees and coming back, restaurants began to take us more seriously.

Speed of light.

It accelerated when we signed our first high-quality restaurant in Barcelona and, later on, McDonald’s in Spain. Those wins validated the model and made it much easier for other restaurants and partners to approach us proactively.

What is your main day-to-day job as CEO?

Today, most of my time is spent on operations. A large part of that is dedicated to structured business reviews. Every semester, I define around 15 to 20 key topics that act as a proxy for our OKRs, and each one has a clear owner. We run monthly, documentation-first meetings for each topic, with detailed written documents and structured discussion. This cadence creates accountability, speed, and alignment across the organization.

Beyond that, my time is spent communicating with the team, hiring, reviewing performance, and handling ad hoc strategic and operational issues. I also see so much potential for Glovo to expand even now. We're looking towards 10x growth in the future. I see a big part of my role as sustaining a culture that is hard-working and driven. Maintaining that kind of energy and work ethic is vital if we are to successfully build the future of online commerce.

What noticeably changed after adopting documentation-first meetings?

It significantly increased discipline across the company and made it much clearer which teams and individuals were underperforming. Performance discussions became more objective, rather than based on intuition or gut feeling.

The format also raised the quality of thinking and execution. Writing encourages clarity, and it’s much harder to hide problems in a written document than in slides. While it requires more mental effort and time to read, the tradeoff has been worth it because it drives faster execution and better accountability.

What’s your philosophy around leadership?

As a leader, I hold myself accountable for driving high-velocity output, day in and day out. Together with my leadership team, I set ambitious OKRs that define where we’re headed, and I push our teams to always move faster, deliver better, and raise the bar every single day. I’m there to drive the company forward by promoting hard work, ownership, and high standards.

When I’m shown a report or plan, my job is to find ways to strengthen it, because saying something is ‘fine’ doesn’t inspire people to push harder. The only way to achieve real growth is through transparency, relentless energy, and consistent drive. I can’t sit back and expect progress to happen on its own.

How has your role evolved over time?

In the early stage, I did everything. I was writing emails and push notifications, setting rider pricing, signing up restaurants, taking support shifts at night, and sometimes even delivering orders. We were extremely scrappy for the first two to three years because fundraising was very hard, and I was constantly on my phone dealing with issues as they came up.

BTS (not that exciting).

As the company grew to around 100–150 people, my role shifted heavily toward fundraising. At that point, the business was scaling rapidly and needed large amounts of capital, so 60-70% of my time was spent raising money and managing shareholders. Outside of fundraising, my main focus was building a strong leadership team to move the business forward.

After the acquisition, fundraising disappeared almost entirely. With only one shareholder to manage, I was able to shift my focus back to operations. Today, most of my time is spent driving execution through structured reviews, working closely with teams, and going deeper into the business again.

What does goal setting look like at Glovo?

Our ultimate goal is to build the future of online commerce, creating a new way of city living that seamlessly connects our physical and digital worlds, where anyone can get almost anything in their city, in their home, within minutes. Every metric we track is designed to move us closer to that goal, and I constantly push our teams to move faster, deliver better, and raise the bar every single day.

The potential for growth at our company is so vast that there’s never a shortage of goals, whether it’s expanding into new Q-Commerce categories, improving the customer experience with innovative features, or building world-class technology. We’re always looking ahead and finding new ways to grow. Everything we do is informed by data, a principle that has served us extremely well so far; when there’s a strong, data-led case for a business decision or a shift in strategy, we act on it decisively.

How do you build culture?

Culture is built face-to-face at the office, through hard work, constant problem-solving, rolling up your sleeves, and leading by example. It's important to always keep the bar high, and the best way to do that is to surround yourself with people more talented than you.

The workforce we've built at Glovo is inspiring; every hire is based on cultural fit. We communicate our company values at the earliest stages of the hiring process. If the prospective employee isn't aligned with and on board with what we, as a company, value most, we know immediately it's a hire that won't work out. I actually hold myself responsible for messing up our culture at one point.

Source.

At around the 1,000-employee mark, I was beginning to get feedback that my communication style was too direct. I felt obliged to tone it down and start speaking more like a politician. The result, however, was a workforce not encouraged to give it their all. I heard from one of our engineers that a rival company approached them, but they declined because "that other company works really hard." That hit me because Glovo needed to be the company that ‘works really hard’ in order to succeed. So it took a bit of a cultural rebuild at that point. We started at the top and worked down.

Some of the team didn't want to return to the work rate of the early Glovo days, and it took about a year of changes in how we worked to turn the situation around. We had to communicate across the board what we expected in terms of work and effort, from the recruitment stage through to the day-to-day running of the company. As a leader, it was my responsibility to add velocity and raise the standards.

How are you thinking about AI on a day-to-day basis?

We see AI as an enabler to make our platform smarter, faster, and more efficient for all our stakeholders: customers, riders, partners, and Glovo teams. AI supports many of our day-to-day operations, both in what users experience directly and in what happens behind the scenes.

On the customer side, AI helps us improve the overall app experience: from how food menus and product categories are organized to how we personalize recommendations or ensure accurate translations across markets. Behind the scenes, it drives automation across finance, legal, operations, and customer support. For example, we use AI tools to process invoices automatically, summarize legal documents, or even train our service agents through simulated conversations.

Across the company, AI is also used to make teams more productive and data-driven. AI is helping engineers code faster, product managers query data more easily, and designers generate content at scale. In short, AI allows Glovo to operate more intelligently and focus our human talent on creativity, innovation, and delivering a better experience for our ecosystem.

What led you to decide to go ahead with the acquisition?

The main driver was scale. In our industry, the biggest players operate on a massive scale, allowing them to invest far more in technology and compete aggressively in specific markets. Even though we had a strong scale in Spain and operated in 25 markets with around €3B in top line, we were still very exposed compared to companies like Uber or DoorDash.

At the same time, there was significant fundraising fatigue. For the first seven years, we raised a new round roughly every nine months, and none of them were easy. The constant pressure, rejections, and uncertainty took a mental toll on the team, the board, and me personally. At a certain point, it felt like the right decision was to secure the value we had built rather than keep putting it at risk.

Was selling the company always the plan? And why did you stay on?

Selling the company wasn’t the original plan. It emerged over time as the industry evolved. As competition intensified and the biggest players pulled further ahead on scale, it became clear that staying independent carried increasing risk. After years of nonstop fundraising and operating under constant pressure, the idea of selling became a rational way to protect the value we had created. It was a gradual shift driven by market dynamics and the realities of sustaining growth in such a capital-intensive industry.

Today, I’m an employee like anyone else, with a normal salary and compensation. The earn-out period ended years ago, so financially, there’s no longer a special structure tied to the acquisition. I report to a single shareholder now, Delivery Hero, which has actually simplified things a lot. There’s more formal reporting and alignment, but it only takes a small portion of my time. The rest focuses on running the business, allowing me to stay deeply involved in operations and execution.

I decided to stay because the industry is still very young and full of opportunity. There’s a lot of growth ahead, and the business remains technically, operationally, and strategically challenging, especially with regulation and margins.

I also have a lot of autonomy to run the company, which is critical for me. As long as the role remains challenging and I can keep building. Beyond that, Glovo is extremely present in daily life in the cities where it operates. Seeing it constantly used by customers, restaurants, friends, and family creates a strong personal connection that makes it hard to walk away.

How do you get the best out of yourself personally and professionally?

For me, it really starts with health. Over the years, I’ve continually raised the bar for how well I sleep and how consistently I exercise because I’ve seen how directly they impact my performance. Having a strong daily routine has become increasingly important, and I make sure to do some form of training before going to the office, even if that means arriving a bit later in the morning. I’ve also learned that variety matters. I used to focus almost entirely on cycling, but I eventually got bored. Now I mix different activities like climbing, tennis, gym sessions, and cycling. That variety keeps me motivated and makes it much easier to stay consistent over time. When I take care of my health and feel physically and mentally energized, I’m far more effective as a leader.

In the end, I enjoy my work. Since the acquisition, I’ve spoken to founders who’ve exited, and what I found was that those who moved into wealth management, away from the grind of running a business, were, more often than not, unhappy.

Solving problems, going to the office every day, and spending time with my team; that is what fulfills me. So, in that sense, getting the best out of myself professionally comes naturally. Right now, it's super clear: work is really important for me. It keeps me going and makes me happy. For me, it's very clear: I will keep working until the day I die.

Extra reading / learning

• Arctic Vaults, AI Agents & The Future Of Dev Tools - June, 2025

• Launching Athyna Intelligence - January, 2026

• Neighbors Feeding Neighbors, At Scale - February, 2026

And that’s it! You can follow and connect with Oscar over on LinkedIn and Twitter, and don’t forget to check out Glovo’s website.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Hyperbound*—the AI sales coach to help you quickly evolve and reinforce your playbooks as you scale.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 2,439 new legends who joined this week! You are now part of a 298,161 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

🏄🏻‍♂️ Eight Very Cool Marketing Things. Insights I've found from around the web in the last weeks.
💨 Blue Ribbon, MJ & The Swoosh: The Nike Story. How Nike was founded, the battle it fought and how it got to where it is today.
🥊 Battle Royale: ChatGPT vs Claude. A closer look into the biggest rumble of our time.

PARTNERS 💫

First impressions matter. With Framer, early-stage founders can launch a beautiful, production-ready site in hours. No dev team, no hassle. Join hundreds of YC-backed startups that launched here and never looked back.

One year free: Save $360 with a full year of Framer Pro, free for early-stage startups. _{*Pre-seed and seed-stage startups, new to Framer.}

With Claude Connectors, Gamma now works natively inside Claude, so you can go from brainstorming to a finished deck without copying, pasting, or rebuilding anything.

This launch removes the biggest friction in AI workflows today: losing momentum between thinking and creating.

Generate, refine, and update presentations without breaking context!

_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

A while back, Anand Arivukkarasu—ex-Meta product leader and one of our advisors—ran an incredible roadmap and positioning workshop that helped shape parts of our direction. He has since evolved that into ProductWorkshop.ai, where he runs focused workshops for startups and enterprises building AI-native products.

Check it here.

If you’re looking for a way to supercharge your AI strategy and want someone who has been at the bleeding edge for a decade or more, check out Anand and what he’s building. Big recommend. Anyway, enjoy today’s post!

BUILDING IN PUBLIC 🔎

How Athyna Makes Remote, Work

Remote work, once the stuff of sci-fi novels, has blossomed into the full-fledged global movement of 'Remotopia laboralis' (/rɪˈmoʊt.oʊ.piə ləˈbɔːr.ə.lɪs/). The post-COVID phenomena have turned kitchen tables into command centres and pyjamas into the new power suits.

My startup, Athyna, has been remote since day one, ~7 years ago, and if anything, you could say we do it well. The gauge I would use in order to signify a company's doing work well is engagement scores. For those who don’t know the term, your engagement score is effectively your culture score.

Vibes.

Engagement scores of 80/100 are considered excellent. Ours at Athyna has been, for the last four or so years, an average of 91. If 80 is excellent and 100 is perfection, we sit somewhere past the midway point between excellence and perfection.

Let’s take a look behind the curtain at how we make remote work work at Athyna.

Guiding principles

Let’s start at the beginning with some general remote work principles we live by at Athyna. While we have a mission, vision, values, and more, and many guidelines in our internal wiki, what I am about to outline is not formally documented anywhere. I am somewhat free-styling the following points. That said, these are the things we (/I) believe are the keys to remote work.

Trust is given, not earned

At Athyna, you are given trust on day one. You can, of course, lose that trust. But we treat people like adults, and we believe people are inherently good. This means we do not (!!) track people’s time, ask them to check in and out, or subject people to any other belittling measures of the same ilk.

2/4 technically not employees. Ok, if you say so.

Happy team.

We don’t really have working hours, either per se. Most will come in around 9-5, sure, but we have always worked on the idea that if you deliver good work in a timely manner, you are golden. Hell, one of our PMs was building a product while hiking the Annapurna Circuit in Nepal. Shout out to Lucho.

Documentation first

We use Notion to document absolutely everything inside the organisation. If it exists and is live, it is either built in Notion or embedded—or, at the very worst, linked—on the correct Notion page.

The idea is that, in any remote organisation, anyone should be able to find anything within seconds. And it should really be inside of two search bars: Notion & Slack. We are not there yet, but we’d be close.

Documenting everything also means having less screen-time burden for the team. Nothing sucks the life out of someone more than meeting after meeting after meeting. You can minimise this by being documentation first.

We share one common language

There is very little flexibility in language at Athyna. We have team members whose native tongue is Spanish, Italian, Portuguese, Filipino, Romanian, and more, but we all share one common language: English. I actually think it sucks how the Western World and English speakers will often think of themselves as Masters of the Universe.

What sucks more, though, is walking into a Google Doc, Notion page, or Slack channel to carry on with your work and not being able to make sense of what’s going on. It’s a terribly un-inclusive feeling, and it just sucks.

Excuse me?

At Athyna, we make sure that in all correspondence, big or small, we speak the one language we all share. This is the one point where I have the least flexibility. And although we have an entire team of people who score 8.5/10 or above in English, we also have an internal English tutor for those who want to continue sharpening their comms.

We do, however, have geo-centric channels (#team-brazil, etc.) where people can talk shit about co-workers during the World Cup and other such events + anything else they may want to chat about.

Remote tech stack

Next, let’s go through the tech that helps us make sure the wheels go round. This is boring, but possibly useful too. As far as our key pieces of tech go, I am going to segment them into two areas: Big Hitters, and Necessary Evils.

The Big Hitters

• Notion: We do everything in Notion. Documentation, OKRs, product positioning, employee directory, pet directory, risk analysis, meetings, reports, advisor updates. If it can be done on any other app, we probably don’t use that app; we do it in Notion.

• Slack: This one goes without saying. Slack does seem to be a bit too distracting sometimes, but for now, it’s very much at the core of what we do.

• Loom: I actually really think the product of Loom keeps getting better and better. Big lover of Loom. Less meetings = happier people. That is much more possible with Loom.

Necessary Evils

• Figma: Figma may actually be rated a bit low. We love both FigJam and Miro for brainstorming sessions and much of our design work.

• Zoom & Google Meet: We try our best to minimise meetings at Athyna, and when we do have them, we make sure they are Speedy Meetings. Speedy Meetings save you an average of 17% of meeting time by presetting your 30-minute calls to 25, 45, 40, 1 hour, 50 minutes, etc.

I have the need; the need for speed(y meetings).

• Google Sheets: Docs are banned at Athyna; we live in Notion, and if it doesn’t require complex formulas, we usually use a Notion database instead. But for complex sheets, we still use Google Sheets.

Meetings & communications

I would love to say we are one of the organisations with close to zero meetings, but we aren’t. We are working towards fewer meetings; however, each department still has meetings. Let’s break down how we run meetings and what communication cadence we use with the entire company.

Departmental Meetings (weekly)

Every department will meet at least once a week to discuss what is important to the department at that time. I think it’s important in a remote setting to have this meeting to get some face-to-face time every week.

Bunch of heroes.

Leadership Meeting (fortnightly)

This call is for senior leadership, including all of our department heads. It’s a big call, but I do like having everyone together in one place to discuss key issues. We structure it as follows:

• Icebreaker: One person presents a question to the group, and we spend 10 minutes sharing our responses.

• Carryover actions: Next, we move to any carryover actions from the previous meetings.

• The Big Issue: We choose one topic from the agenda to spend the most time on. We probably spend 20-25 minutes here.

• The remaining agenda: And finally, we tick off the remaining items. For anything that is missed, we try to address async in Slack.

It’s worth noting that all agenda items are posted in the #agenda-department Slack channel with a paragraph or two of context, so everyone can mentally prepare.

All Hands (monthly)

Our monthly All Hands happens on the second Monday of each month and wraps up the prior month. I present these for the most part. We go through key metrics, good, bad, and the ugly, and the new hires, roles, charges, etc., before moving on to a departmental presentation. Following our department presentation, Taina, our HR leader, will speak on some people and culture topics, then we will finish with a team Q&A.

Meeting Free Friday (weekly) And finally, every week, we have a deep work day on Friday. It’s blasphemous, or downright illegal, to book a call with a colleague on this Friday.

Allies & Investor Update (monthly)

We send monthly investor updates to investors, allies, and potential future investors at Athyna. Our VP of Operations, Bea, prepares these with me, and they go out between the 1st and 31st of every month, ha. But they always go out.

Agora Sessions (monthly)

Every month, we also have a special session we call our Agora Sessions, which focuses on learning a skill from a team member. Think of it as a sort of lunch-and-learn. We have had astrology, cinematography, the synergy of hip-hop & skateboarding, and even a cooking class with our very own Julia Gerardo Luna.

Walk & Talk Meetings (weekly)

I thought it might be worth adding that some teams, including mine, like to use walking meetings in their weeks. Away from screens, unless otherwise coordinated, we will usually walk our dogs, drive down the shopping centre, or go for a slow bike ride in the park. If it’s good enough for Steve Jobs, it’s good enough for me. Another example of us betting on fewer screens making for happier humans.

Hiring & location-ing

When building remotely, it’s important to have a strategy around how, who, and where you plan to hire. For us, we wanted to have hubs around the world. Places where, although remote, people could get together if and when the chance arose.

We did this well originally, setting up hubs in South America and South East Asia, but it soon got a little out of whack. Our first head of talent being Argentine meant most of our team became Argentinian. To be honest, most of our team are still Argentinian, and now Brazilian, including most of our leaders. Argentina and Brazil are some of the richest talent hotspots in the world, and they have next to no cultural differences.

Ziggy during WC 22.

We have slowed our hiring in Argentina for the moment to referral-only, so that we can build out hubs two and three. Today, we hire more heavily in Brazil and have a significant team there. The reason it’s important for us to diversify our team is that I never want people to feel less than inside our company. And if we have 80% of our team in one location, it starts to feel a little like that.

Building culture remotely

This is a really funny one for me. I vividly remember the early days of Athyna, when I was having a conversation with Carmela, our first head of culture, and I was stressing about how we were going to bring the team together. Carmela shook her head at me and said something I’ll never forget.

The statement hits me like a ton of bricks, and I stand by it today. I don’t think thereis any link between building team engagement and seeing people in person. Seeing co-workers face-to-face is awesome. But it’s totally uncorrelated to building culture. At least this has been my experience.

Athyna’s most recent engagement score.

That being said, I am sure many people find ways to fuck it up. Here are a few things you can look at to make sure you're not one of those who don’t.

Make everyone an owner

We give equity at Athyna to everyone, from executive to intern. And we don’t offer options that someone would need to buy to access. We give RSUs. Giving RSUs is the equivalent of gifting stock to your team at no cost. Options for most young people are often prohibitively risky and/or expensive. They are bogus, really. We give RSUs.

And we also built a second trigger into our plan, meaning the shares don’t vest until a) time and b) a liquidity event has happened. This means there is no taxable event (ever!) until someone has liquidity in their stock. BOOM!

Help people build their careers

People are ambitious. Help them get to the next stage of their career. Whether that is within your org, outside of it, moving up a ladder, or across to a totally different area. This is your job as the leader of an organisation. Help your people thrive.

We have had salespeople turn into product managers, CS people move into culture, graphic designers turned UX, and much more. Add to that, we have had people with little to no experience grow into leaders of our organisation.

Research by PwC showed that 43% of employees leave their jobs due to a lack of career growth opportunities. While a sideways move might not directly lead to promotions, it can demonstrate your commitment to career development.

Not only is it great for your people, but it’s also one of the things that, unless you are slightly evil, will fill your heart with little bundles of joy. Take this seriously!

Don’t f**k around

I could have called this title ‘Lead by example’ or ‘Act with integrity’ or any number of other titles, but I simply would not have been able to use my favourite meme of this edition. This one.

Mission accomplished.

In all seriousness, though, your job is to be a leader. How you act is how your people will act. Our corporate motto at Athyna is ‘What Would Ned Stark Do?’ And people get it. They are expected to act with integrity and do the right thing at all times, but the moment you don’t uphold your end of the bargain here, neither will your team. Act accordingly.

In sum

Remote work isn't a consolation prize for companies that can't afford an office. Done right, it's a genuine competitive advantage: access to world-class talent, lower overhead, and, if you're intentional about it, a culture that punches well above its weight. Seven years in, a 91 engagement score, and a team spread across a dozen countries, Athyna is proof that the kitchen table can be just as powerful as the corner office. You just have to be deliberate about it.

Me and some Athyna team.

The playbook isn't complicated. Trust people, document everything, meet less, and remember what Carmela told me all those years ago. Culture isn't built at the water cooler. It's built into how you show up for your people; every day, across every time zone, whether they can see you or not. Get that right, and the rest is just tools and calendars.

Extra reading

• GitLab Handbook, All Remote - 2023

• The Remote Handbook, Tyler Denk - January, 2024 - (need to subscribe to read)

And that’s it! You can find more about how Athyna can help you to build a high-performing global team here.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Hyperbound*—the AI sales coach to help you quickly evolve and reinforce your playbooks as you scale.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 24,387 new legends who joined since our last edition! You are now part of a 295,722 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

💨 Blue Ribbon, MJ & The Swoosh: The Nike Story. How Nike was founded, the battle it fought and how it got to where it is today.
🥊 Battle Royale: ChatGPT vs Claude. A closer look into the biggest rumble of our time.
🎊 Unfiltered: Tracksuit Put Brand Back On The Map. The unpolished conversations, early chaos, and brand decisions that shaped the company.

PARTNERS 💫

CRMs only work if you keep them updated. Founders don’t have time for that.

Lightfield is the AI-native CRM built for startups. It automatically captures emails and meetings, keeps every record up to date, and surfaces follow-ups with zero manual entry. No logging. No cleanup. No lost context.

First impressions matter. With Framer, early-stage founders can launch a beautiful, production-ready site in hours. No dev team, no hassle. Join hundreds of YC-backed startups that launched here and never looked back.

One year free: Save $360 with a full year of Framer Pro, free for early-stage startups. ^{_{*Pre-seed and seed-stage startups, new to Framer.}}

_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

_{*Note: Political rant incoming, if you are a Trumper, you'd best look away now.}

As someone who thinks Trumpism is very dangerous for the world, it’s been fun watching him destroy the GOP's chances in the midterms, along with JD’s chances in 2028. A lot can change in the next 2.5 years, but I couldn’t think of a bigger voter betrayal than what we’ve seen in the first 15 months of his term. We’ve had economic destruction, backing out of free trade, a pedophile ring cover-up, and now a brand new unnecessary war. Poor old Sacks mustn’t know what to do with himself.

Trump has also been played by Putin like a fiddle and absolutely dogwalked by Netanyahu. It sucks that he has been so destructive both domestically and internationally. I do hope that at least we are cleansed of him and his ilk for good. We, as a global community, deserve much better than this.

BUSINESS STORY 🗞️

Eight Very Cool Marketing Things

My father has one of those garages that has a million and one little trinkets from all over. Shells from some faraway beach, old motorbike parts from a discontinued bike, posters and pin-ups from the 1983 AFL Grand Final (Aussie reference). Me, not so much. I’m not so much of a collector of things.

As an entrepreneur, marketer, and all-around growth hacker, though, I do collect ideas. My bookmark folders are overflowing, and my swipe files can take no more. All digital gold I have found across the World Wide Web, that I believe one day, will move me one step closer to complete, and utter global domination.

My preciiouuus.

Today, I am going to share a few of these with you, with the hope that you, like me, may be able to find some inspiration; a small win that gets you to your next milestone. Precious nuggets of inspiration are all around us. Here are a few I find compelling. Enjoy!

1/ The creativity of this McDonald’s ad

First up, we have a wonderful advertising campaign by Mickey D’s. It’s usually Burger King that I sing the praises of in this newsletter for their incredibly precise global newsjacking tactics, but today it’s Ronald’s team. I am not going to talk too much about this ad. Just pause for a moment and look closely, and you’ll see the beauty for yourself.

Source.

2/ Using a media platform for lead gen

One of my goals for next year is to begin leveraging this newsletter more deeply for lead generation. My company, Athyna, launched our Intelligence product a few weeks ago and has been pulling out all of the stops to build a pipeline in the AI post-training space.

With that in mind, one of the things you’ll start to see over the next few months is more and more guests from our Dream 100 clients. If you’re not familiar with the Dream 100, it’s an exercise of writing down the 100 clients you want to work with and directing as many resources as possible towards them. In our case, we have 123 odd firms, and four or five contacts inside of each of them. You can see our full list here.

See our here.

Our targets on the list range from developers and architects to CTOs. And as you well know, if you’ve ever done technology sales before, these are not the easiest people to get in front of, let alone be able to build rapport with. But if Dale Carnegie taught me anything, it’s that spending 30 minutes with someone and genuinely picking their brand usually leads to the beginnings of a good relationship. As an example, last week I interviewed Benny Chen from Fireworks AI. The piece will come out soon, but in the meantime, I sent him this message. Let’s see how it goes.

A note on the above

Something interesting for any reader connected in the AI space: we are offering equity for introductions to anyone in our Dream 100. $25k equity for anyone who can introduce us to the right contacts at companies like Anthropoc, OpenAI, Midjourney, etc.

We will also be offering a kicker of $50k equity per client we onboard to our Intelligence product. If you are connected to a load of contacts in the AI space, reach out to me here. I’d love to chat with you and get you involved.

3/ Small elements of brand affinity

Something else I’ve been loving lately is the idea of small brand touchpoints that add a little brand affinity. You would have seen brands that have built playlists—Tyler Denk from beehiiv, for example, has Big Desk Energy—or other small brand touchpoints for their community. Another thing that I love are deep work playlists.

A good, deep work playlist is one that just loops for hours on end, alongside you, while you waltz through a nice flow state. I usually use pixelated Lord of the Rings or Game of Thrones versions myself, but I’ve been playing with the idea myself, and will soon be shipping Open Source versions. You can see below my Elon hurtling through space in his Roadster, and Bezos deadlift PR animations. All we need now is the track to put beside, and voila. Brand affinity touchpoint.

4/ Trevor from Torq

Another fun one I found recently was Trevor from Torq. Trevor claims to be a junior media intern at the Series D cybersecurity unicorn, but really, what Trevor is is an old-fashioned hype guy. You know the buddy you want around you at the party your crush is at because he’ll tell all the best stories on your behalf; that type of hype guy.

Source.

Funny thing about Trevor is, he’s actually a paid actor. He’s paid to make noise online, film content at conferences, and more or less just be a viral sensation for the brand. Everybody needs a hype guy. Every company needs a Trevor.

5/ Timely 1st party data journalism

One of my favorite brands on the planet for straight-down-the-middle, unbiased reporting on global news is Tangle. They are an audience of over 500,000 readers from fifty countries and rate incredibly highly on every media bias and factuality chart.

But I digress. What I love about Tangle is its first-party data journalism. Every Sunday, they send a wrap-up email with a handful of key headlines that happened Monday through Friday. They cite the event, their take, but the most important thing is the data they poll their audience on. It’s, honestly, a fascinating look at how real-world events are perceived in a non-partisan way. This is another example of something I’d love to do with this newsletter. A pulse check on the happenings in tech.

Source.

6/ Next level memetic warfare

What seemed like mere minutes after Trump and Hegseth started dropping bombs on Iranians, the internet, as it is wont to do, was ablaze with memes about the news, my favorite of which was a parody of Flock of Seagulls, "I Ran." Click the link, and you’ll see what I mean. My question is: How does one do this?

This level of memetic warfare on the battlefield of distribution is game, set, match level stuff. If we are all in a war of attention, the MTV music video parody meme wins.

Source.

7/ Polymarket’s interactive advertising

It pains me to say this—Polymarket and Kalshi, along with their shit-eating founders, are my most hated companies in tech—but the marketing team at Polymarket needs a raise. Not only for the run of back-to-back-to-back partnerships they launched recently and for their Mamdani-inspired free grocery store, but also for this cracking interactive ad they ran in the New York subways.

Recently, Avi Schiffman, the guy who launched the dystopic dumpster fire Friend.com, burned $1 million on subway ads, leading to them being defaced by all the human-first passersby. Polymarket saw this (I assume) and went one better. Rather than build a negative sentiment campaign, they instead made a predictions board for a number of real-life events.

Will Marty Supreme win Best Picture? What price will Bitcoin hit in 2026? Who should win the next election? They are doing two things here: 1) aligning with the brand of making predictions, and 2) inviting graffiti, UGC, and even a viral moment. I despise this company. But game gotta recognoze game sometimes.

8/ “I can’t hire fast enough” messaging

Alex Liberman, one of the co-founders of Morning Brew, seems like a good guy to me. One of those online personas that you cannot help but like. Alex is doing something online with his new Tenex Labs startup that fascinates me: he is bragging. Bigtime.

It is my sneaking suspicion that whether or not Alex is telling the truth about their hiring, this strategy, especially when you have a large audience, works as a self-fulfilling prophecy. ‘We are crushing it, we cannot keep up with demand,’ etc., fills people with curiosity, and is a soft signal that this company is hot. A social proof self flex.

Source.

Source.

AI pulls two emotional triggers in people. The first being desire: the need to be adept and on the cutting edge of this new technology. But also the more powerful emotion of fear: the fear of being outcompeted to failure. I really do like this guy, and he’s probably telling the truth. I wish him all the best. What I do know is that come Monday, you’ll see a post from me talking about how we cannot possibly hire enough people to keep up with demand.’ Advantage me. Thank you, señor Liberman.

Adios

That’s all for today. I actually started the day with a post about how to train LLMs, but I’m tired, and my limited cerebral horsepower wasn’t up to it, so you got this fluffy little fun piece.

Signing off just before midnight Saturday night, my time, getting this scheduled so I can enjoy my Sunday, which also happens to be my five-year anniversary. As always, thanks for reading and lots of love!

Extra reading

• The Ultimate Founder Mental Health Stack - August, 2024

• Pattern Interrupt Marketing, What Is It? - October, 2025

• How To Read Like The Greats - December, 2025

And that's it! You can follow me on Twitter and LinkedIn, and also don’t forget to check out Athyna while you’re at it.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Tracksuit*—a modern brand-tracking platform that shows how your brand is growing, how people feel about it, and where you’re winning (or not) in the market.

beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 2,346 new legends who joined this week! You are now part of a 271,335 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

🥊 Battle Royale: ChatGPT vs Claude. A closer look into the biggest rumble of our time.
🎊 Unfiltered: Tracksuit Put Brand Back On The Map. The unpolished conversations, early chaos, and brand decisions that shaped the company.
🧠 Inference Engineering, Open Models & Shipping AI At Scale. An interview with Philip Kiely, Head of Developer Relations at Baseten.

PARTNERS 💫

With Claude Connectors, Gamma now works natively inside Claude, so you can go from brainstorming to a finished deck without copying, pasting, or rebuilding anything.

This launch removes the biggest friction in AI workflows today: losing momentum between thinking and creating.

Generate, refine, and update presentations without breaking context!

Framer is the design-first, no-code website builder that lets anyone ship a production-ready site in minutes. Whether you're starting with a template or a blank canvas, Framer gives you total creative control with no coding required.

Add animations, localise with one click, and collaborate in real-time with your whole team. You can even A/B test and track clicks with built-in analytics.

_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

A lot has changed since my last update on my quest to become the best weightlifter in tech. We launched Athyna Intelligence, grew enterprise by 15%, built out our internal AI team, and grew by roughly half overall. All while this newsletter went from 50k to 250k subs, helped a company with its IPO, sent my first $150k proposal, and built a team for the newsletter. It’s been a busy time.

Source.

This week, amongst the busy life of being a founder, I hit a 10-year snatch PR of 103 kgs. So, I’m proud to say that my quest for 120 kilo snatch and 150 clean & jerk is very much alive. The best decision I have made in a long time was carving out non-negotiable time doing what I love: weightlifting.

DEEP DIVE 🕵🏻

Phil Knight - Co-Founder at Nike

Philip Hampson Knight (born February 24, 1938) is an American billionaire business magnate who is the co-founder and chairman emeritus of Nike, Inc., a global sports equipment and apparel company. He was previously its chairman and CEO.

In December 2023, Forbes estimated his net worth at $45 billion. He is also the owner of the stop-motion film production company Laika. However, Knight is most famous for sparking one of the greatest debates in history: Is it pronounced Nike or Nike-E?

These shoes are still fire today.

Today, we’ll take a deep dive into the story of one of the most loved brands in the world and a founder who was so determined to make it work that his drive and passion transformed the sports industry forever. Let’s explore the journey of Phil Knight and the rise of Nike, from humble beginnings to a global powerhouse.

Early Knighthood

Knight was born in Portland, Oregon, to Bill Knight, a lawyer-turned-newspaper publisher, and his wife, Lota Cloy (née Hatfield) Knight. As a youngster, he grew up in the Eastmoreland neighbourhood and attended Cleveland High School. One of the factors that played a part in Phil’s success later in life was apparent at a young age. He was born with one part stubbornness, one part drive, and one part competitiveness.

This competitive drive also led him to sports. In Phil’s case, it was running. And running for the famed Oregon track and field program at the University of Oregon. He was part of the track and field club under famed coach Bill Bowerman during this time. Bill, with whom he would later co-found Nike.

University of Oregon image. No idea which is Phil.

Phil was a relatively high performer at U-of-O; his personal best middle-distance time was 1 mile in 4 minutes, 13 seconds, and on the education side, he earned his business degree in 1959 in just three short years.

Bowerman, Blue Ribbon & Onitsuka

Once Phil finished school, he enlisted in the Army, serving 12 months of military duty before shipping himself off to Stanford Graduate School of Business. It was at Stanford that he would go on to produce a paper titled "Can Japanese Sports Shoes Do to German Sports Shoes What Japanese Cameras Did to German Cameras?", effectively foretelling what was to come.

Sure enough, what came next was a world trip, but most importantly, a trip to Japan. While not studying the Japanese food culture, Phil was able to hike to the summit of Mt Fuji, and also stop off for a visit at the Onitsuka shoe factory in Kobe, which was producing Adidas knock-offs, called Onitsuka Tigers.

The Tiger himself.

_{*Yes, these are the yellow shoes + jumpsuit combo made famous by Uma Thurman in Kill Bill.}

Phil was so enamoured with the quality of the Japanese shoe design that he called Mr. Onitsuka himself, who agreed to meet with him. By the end of the meeting, Knight had secured Tiger distribution rights for the western United States.

The first Blue Ribbon Sports.

Once he was home from Japan in 1964, the 26-year-old Phil started pushing Tigers from the back of his green Plymouth Valiant at track meets across the Pacific Northwest. Seeking validation and maybe a new client, Phil sent the Tiger shoes to his old track coach, Bill Bowerman. To his surprise, not only did Bowerman, whom he respected greatly, like the show, but he liked it so much that he asked to join the business.

On January 25, 1964, with a cash injection of just $1,200, Phil and his old running coach shook hands and went into business together. The birth date would be that of Blue Ribbon Sports, the distribution company that would go on to become the Nike we know and love today.

Taking on the Tigers

The partnership between Blue Ribbon and Onitsuka started strong. Knight and Bowerman were distributing Onitsuka Tiger shoes all across the US. And the shoe was growing in popularity for its innovative design and quality.

As demand grew, so did the ambitions of Knight and Bowerman. They dreamed not only of distributing shoes but also of creating their own. A brand that they believed could revolutionise the athletic footwear market.

Swoosh?

Tensions began to simmer beneath the surface. The rumour was that Onitsuka was planning to sever ties with Blue Ribbon. They wanted to replace them with new distributors to cover the growing U.S. market. Feeling cornered and betrayed, Knight and Bowerman decided to do what all good, ambitious founders do: take matters into their own hands.

In a totally risky move, the duo started developing its own line of shoes. Bowerman's expertise in track and field and his relentless pursuit of innovation meant they designed shoes that were not only high-performance but also stylish. The same thing Nike is known for to this day.

The breaking point came when BRS accused Onitsuka of a major breach of contract. This led to a legal battle that would determine the future of both companies. In the end, though, Blue Ribbon would emerge victorious. This was the official end of the partnership with Japan.

The birth of Nike & the ‘Waffle Sole’

After the dustup with Mr. Onitsuka and his Tigers, Knight and Bowerman wanted to distance themselves from Onitsuka. This meant a new brand: name, logo, and all. Phil had his favourite, ‘Dimension Six,’ which he thought had a futuristic and innovative ring to it. Luckily, his colleagues hated it.

Fellow running geek and first employee of Blue Ribbon, Jeff Johnson, proposed a name that came to him in a dream: Nike, for the Greek winged goddess of victory. Nike. Hmm, that has a nice ring to it, the team agreed. Then and there, on the date of May 30, 1971, Blue Ribbon became Nike.

Next was a new logo. Carolyn Davidson, a graphic design student at Portland State University, was given $35 to to design something new. Something that Phil said “needed to convey motion and speed.” Davidson presented a number of designs. One design, a curved checkmark dubbed a ‘swoosh,’ won out. Knight begrudgingly accepted the swoosh for no other reason than that they needed a logo quickly.

The most famous logo-mark in the world today, seen on the feet of one in three people you cross by in the street, cost $35. And was created by a graphic design student. Incredible.

That same year, Bowerman, Nike’s own mad scientist, created the first sneaker soles with a ‘waffle’ grip, quite literally cooking them in a waffle iron.

One of these men is Bill Bowerman.

Nike sold $3.2 million worth of shoes in 1972 with their patented ‘waffle sole,’ and its profits doubled each of the next 10 years. In 1980, Nike passed Adidas to become the industry leader in the United States, the year it went public.

‘Sometimes I dream…that he is me…’

The year is 1984, and a 21-year-old Michael Jordan, the third pick of the NBA draft, is about to don the hardwood wearing his very own black and red Air Jordan 1s. Sounds normal today, but this was far from normal in more ways than one.

Firstly, it was Nike’s first-ever signature sneaker. A massive bet for an unknown rookie from Wilmington, North Carolina. Secondly, they were breaking the NBA uniform policy. At this point in time in the NBA, you had to be vanilla. You needed to wear shoes that matched their team's uniforms and contained a significant amount of white.

The shoes that shook the world.

The NBA told Nike that if Jordan wore his black-and-red kicks, he would be fined $5,000 each time he set foot on the court. Instead of conforming, Nike decided to embrace the controversy. They paid the fines on Jordan's behalf and used the story as a powerful marketing tool.

_{*Whether or not the NBA actually fined Jordan is still disputed today.}

What happened next was a surprise even to Phil, Nike, and even Sonny Vaccaro, the ardent Jordan supporter who pushed Nike to sponsor the young superstar. Jordan would win the Rookie of the Year, and go on to be looked at as the greatest to ever do it. But the same can be said for his shoes.

Powered by Jordan's dual three-peat championships and huge cultural appeal, the Air Jordans sold so well that, in 1997, Jordan Brand was officially founded as a subsidiary of Nike. In 2023, the Jordan Brand generated $6.6 billion in revenue, accounting for 12.8% of Nike's total revenue of $51.2 billion for the same year.

Nike would successfully run the Jordan playbook of finding the hottest stars, set to dominate their sport, over and over and over again. Ronaldo, Serena, Rafa, LeBron. All Nike.

Another of their most successful athlete partnerships was penned in 1996, with a 20-year golfing phenom by the name of Tiger Woods. A partnership that spanned 27 years, and actually just came to a close earlier this year.

Damn straight.

Nike was really one of the earliest influencer marketers. Through Phil, their creative team, and their athletes, they created an allure—similar to Apple's—that they still hold today.

Nike is cool, and all the cool kids wear Nike.  

"Phil understands the symbolic power and attractiveness of sports," says A. Michael Spence, dean of the Stanford Graduate School of Business and a Nike board member. "And he helped build that connection in our culture.”

Setbacks and controversy

For all their successes, Phil and Nike have been without their fair share of controversy. In a positive sense, they have always been able to leverage some controversies into positives, case in point, the Air Jordan 1s colorway controversy. But there have also been a multitude of controversies that have really made people stare down at their feet and think, ‘why.’

Good controversy

• Colin Kaepernick campaign (2018): Nike's decision to feature Colin Kaepernick in its ‘Just Do It’ campaign drew both praise and criticism. Sure, it sparked a backlash from some consumers, but it also resonated strongly with its younger, more progressive audience. Nike saw a spike in sales and demonstrated a commitment to social issues.

Serena Williams' Catsuit (2018): In the same year as Kaepernick, the French Open banned Serena Williams from wearing her black catsuit attire. Nike responded with an ad featuring Serena and a powerful tagline.

• Nike's environmental and sustainability initiatives: Over the years, Nike has introduced a number of initiatives to improve its environmental impact. Their ‘Move to Zero’ campaign, for example, aimed at achieving zero carbon and zero waste. These efforts have been well-received and have turned the brand's overall sentiment from negative to somewhat positive.

Bad controversy

• Sweatshop labor and poor working conditions (1990s-2000s): Nike has faced numerous controversies, large and small, over the decades, but never more so than when it faced severe criticism for using sweatshop labor in countries like Indonesia and Vietnam. Reports showed poor working conditions, low wages, and child labor. This led to global protests and damaged Nike's brand reputation.

The most damning of all was the 1997 Life magazine article by Sydney Schanberg titled "Six Cents an Hour," in which the author travelled to Northern Pakistan to see some of the reported practices firsthand.

“It’s an age-old practice,” Nike spokeswoman Donna Gibb would say in response to the piece. “And the process of change is going to take time. Too often, well-intentioned human rights groups can cause dramatic negative effects if they scare companies into stopping production, and the kids are thrown out onto the street.”

Six cents an hour.

Although the reporting through the 90’s and early 2000’s was jarring, Nike has worked hard since to improve conditions and overall transparency in its supply chain.

Still ‘doing it’ today

Nike introduced its ‘Just do it’ slogan in a commercial featuring 80-year-old runner Walt Stack in the year 1988. Nike today is living that slogan, and is—aside from the odd slip-up, and pressure from up-and-comers—as culturally relevant as any time in the past.

And their revenue slowly but surely moves up and to the right, with 2025 revenues of $51.4 billion U.S. dollars. They remain relevant thanks to the power of their brand and collaborations with artists and designers such as Virgil Abloh (Off-White), Travis Scott, and sacai. But they are also innovating.

Source: Statista.

The NFT and web3 craze is one of the best examples of a bunch of snake-oil salesmen being fooled by smoke and mirrors in the last century, but Nike was at the forefront of innovation. In December 2021, Nike acquired RTFKT Studios, a leading brand that leverages cutting-edge innovation to deliver next-generation collectibles that merge culture and gaming.

Nike also established a strong presence in the metaverse. This included creating virtual environments where users can interact with Nike products, participate in virtual events, and even purchase virtual goods. Nike’s total NFT revenue was recently reported at $185M, with the next-best brand, Dolce & Gabbana, at a paltry $25M.

Source: Ledger Insights.

Whether or not you believe in the future of the Metaverse, the value of NFTs, or the general shit-show at the fuck factory that seems to be web3, what this shows is that Nike refuses to be left behind. This is a legacy built behind a waffle iron that Phil Knight and Bill Bowerman used to revolutionise running shoes, and it's still pushing boundaries with every step today.

Phil-osophy

You don’t create a category-leading brand without incredible leadership. Which is interesting considering some of the ways Phil led throughout his long career. For example, Nike had a few part-time sales reps working across the country. One of them, Jeff Johnson, kept sending letters about all sorts of matters. Phil rarely replied.

Mayor of Zero Fucks County.

This is not what they teach you in business school. But you cannot deny that it worked. Let’s take a quick stroll further into the mind of Phil Knight in his own words.

Playbook, how Nike grew

Be an innovator

From the waffle iron to the metaverse to power-lacing sneakers, Nike has pushed the boundaries. From its inception, the company sought to develop cutting-edge athletic footwear and apparel.

The introduction of Nike Air technology in 1979 is one game-changing example. Developed by aerospace engineer Frank Rudy, this innovation meant embedding air-filled bags in the soles of shoes to provide cushioning and support to athletes.

Market masterfully

Nike, put simply, is among the short list of the greatest advertisers in history. Do a quick Google of ‘greatest advertising campaigns in history,’ and you will see the swoosh alongside the likes of Apple’s groundbreaking 1984 campaign, De Beers’ a diamond is forever, and Red Bull sending Felix Baumgartner skydiving from outer space.

Not only have they been able to conjure up some of the great campaign thematics of all time, but they have built a brand that athletes and celebrities want to be a part of.

Expansion and diversification

Nike's origins lie in athletic footwear, but the company has diversified into apparel, equipment, accessories, and more. Today, Nike is not only synonymous with running and ball sports, but also with skateboarding, golf, and more. This expansion has been crucial to Nike sustaining its growth long-term.

Source.

But it’s not only diversifying, but it’s also offering—Nike is geographically diverse—with approximately 57% of the company's total revenue coming from outside the United States in (year ending May) 2025. And Nike's acquisition strategy has also played a role in its growth.

_{*What the heck is ‘Greater China’ anyway?}

In 2003, Nike acquired Converse, the iconic footwear brand known for its Chuck Taylor All-Stars. This acquisition meant Nike could diversify its portfolio and reach new customers. Similarly, the acquisition of Hurley in 2002 and the purchase of Umbro in 2008 (later sold in 2012) expanded Nike's presence in the action sports and soccer markets, respectively.

Adapt as necessary

Nike’s knack for adapting to market trends and embracing digital transformation has played an important role in their success. They’ve used tech to enhance customer experiences, streamline operations, and drive innovation.

The Nike+ launch in 2006, in partnership with Apple, was the start of their digital journey. Integrating sensors into running shoes to track performance and syncing data with an iPod was revolutionary.

This evolved into the Nike Training Club and Nike Run Club apps, offering personalised training plans and community features.

Lately, Nike’s all-in on digital transformation through its direct-to-consumer strategy. They’ve poured resources into e-commerce and mobile apps, allowing customers to shop online and snag exclusive products. The pandemic accelerated this, making digital sales a major part of Nike’s revenue. With data analytics and AI, Nike’s nailed personalised marketing and boosted customer engagement.

Protect the value of the brand

The value of Nike lies in its brand. The name, the swoosh, the athletes. But more than anything, it lies in the feeling Nike gives you. The love you subconsciously hold for it. Because of this, Nike works hard to protect the brand. What does protecting the brand look like today: sustainability.

The ‘Move to Zero’ campaign, launched in 2019, underscores this. Move to Zero is Nike's commitment to achieving zero carbon emissions and zero waste. To achieve this goal, Nike developed new and innovative materials and manufacturing processes, such as its Flyknit technology, that reduce waste by using a single piece of fabric for the shoe's upper. The company has also increased the use of recycled materials in its products and packaging.

But Nike's sustainability efforts go beyond just product innovation. The company has new initiatives to improve labor practices and working conditions in its supply chain. Nike's transparency reports and partnerships with organisations like the Fair Labor Association reflect its commitment to ethical and responsible business practices.

Without measures like this, the brand would atrophy. And if the brand atrophies, so does revenue and so does Nike overall. This is of the utmost importance for Nike to remain relevant today.

Legacy

Phil Knight, born and bred in rural Portland, Oregon, was a larger-than-life figure. A passionate entrepreneur who worked his way from a lowly shoe salesman to a major shareholder in one of the greatest businesses in modern history. And he did it through passion, resilience, and drive.

Phil’s reign at the top of Nike is not without fault. The business practices employed in Asia are the biggest stain on his resume. But in Phil’s defence, he did not build the system; he simply took part in it.

What matters is how he responded, and Nike has responded by aiming to be a leader in global manufacturing and outsourcing. Overall, this is the story about a man who took on the world and won. Even if he wasn’t perfect, his legacy is one of enduring impact and transformative innovation.

Fun facts

• Voice history: The ‘Just Do It’ slogan, beyond its cool origin, was first voiced over by none other than actor Shia LaBeouf in a Nike ad.

• Most expensive sneakers: A pair of solid gold OVO x Air Jordans was valued at over $2 million.

• Ben Affleck as Phil: Hollywood A-Lister Ben Affleck played Phil in the 2023 film Air, which chronicled the Nike and Air Jordan story.

• Nike’s Moon Shoe: One of the first Nike shoes ever made was nicknamed the ‘Moon Shoe’ because of its waffle sole that left tracks similar to those on the moon. Only 12 pairs were ever made.

• MBA thesis insight: The idea that sparked Nike was actually from Phil Knight’s MBA thesis, where he argued that shoes from Japanese factories could compete with German brands.

• Nike Air technology: Nike’s Air technology was inspired by aerospace engineering and features pockets of pressurised air within the shoe's midsole.

Extra reading

• High-Performance Marketing: An Interview with Phil Knight - August, 1992

• Shoe Dog, Phil Knight - April, 2016

• The Best Nike Ads Of All Time - July 12, 2023

• A Statistical Analysis of Nike’s Rise to the Top - April, 2024

And that's it! You can follow me on Twitter and LinkedIn, and also don’t forget to check out Athyna while you’re at it.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

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TOOLS WE RECOMMEND 🛠️

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beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

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🎊 Unfiltered: Tracksuit Put Brand Back On The Map. The unpolished conversations, early chaos, and brand decisions that shaped the company.
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HOUSEKEEPING 📨

I’m thinking of doing a rebrand of the newsletter, with Aerolab, a close partner or ours, and the firm who recently did Athyna's rebrand. They are the best branding and UI agency in South America. Below is the first moodboard I liked the most.

The thing is though, I am really sad to say goodbye to the current brand. I have this really strange feeling. Something I’m not super familiar with. I think I need to keep as much of today’s brand as possible. I am incredibly attached to it. The stupid memes, cultural references, terribly loud color scheme. What do you think?

Either way, there will be some level of improvement to the branding. But I definitely do have a very strong emotional pull to what I’ve created to this point. Such is life I guess. Here’s to you enjoying today’s post dear reader.

GUEST POST 💄

Battle Royale: ChatGPT vs Claude

Ali versus Foreman, Coke or Pepsi, Lannisters and House Stark. What do they all have in common? War. Whether in the ring, on the S&P 500, or in the fields of Westeros, these famous names went head to head against one another in all-time blood feuds, while we all sat back and watched with popcorn in hand.

Today, a new struggle is waging in the silicon streets. This time between AI giants OpenAI and Anthropic. They’ll tell you it’s to create one almighty omnipotent God-like, super AGI. It’s not. This is an all-out market cap war. And just like all good bust-ups, this one has a surprise around just about every corner.

The animus is palpable.

Dario Amodei, prodigal son of OpenAI, left the company in 2020 due to its direction to found rival Anthropic a year later. Shortly after the Sam Altman saga hit fever pitch with Sama’s firing, hiring, re-firing, and rehiring. Now the two are stuck in a duel to be the most exciting company in the world. Two years ago, OpenAI had what looked to be an insurmountable lead; today, most are betting on Anthropic.

Today, we are going to look at the narrative between the two firms. And to do this best, I have enlisted my buddy, Isaac, who runs Pistachio and also writes the Brand Chemistry newsletter. He’s a much wiser man than I, so this should be a fun one. Over to you, Isaac.

The Battlefield

Hey, Isaac here. You might’ve seen that both ChatGPT and Claude launched their first-ever brand campaigns recently. Way more than the product demos or feature announcements we’re used to, these were actual brand campaigns with cinematic footage, music, and emotional storytelling.

After years of competing on benchmarks like who has the longest context window or the best reasoning capabilities, they've both suddenly pivoted to selling feelings instead of features. The timing is anything but coincidental. AI is crossing a significant threshold. It's moved beyond tech-y early adopters and entered the messy territory of mass-market adoption, where emotional connection matters more than capability.

One brand positioned AI as your everyday assistant, making mundane tasks easier. The other positioned it as your thinking partner for meaningful challenges. Very different approaches. Which raises the obvious question… which one will win the AI brand war? Time to choose your fighter.

ChatGPT: making AI feel normal

ChatGPT's campaign opens with a young bloke doing pull-ups at sunset. The camera pulls back. Text floats up like movie credits, saying, "I want to feel stronger, help me do some pull-ups by autumn". ChatGPT's response scrolls up the screen with a workout plan.

The whole thing is shot on 35mm film. It looks more like an indie film festival entry than a tech commercial.

Their Head of Marketing said they wanted to show how ChatGPT can make your life easier and help you do more of what matters. Better search. Better answers. Everyday utility. The emotion they're selling is accessible productivity*,* AI as Google 2.0, useful for the mundane tasks anyone might encounter. It's a logical pivot. ChatGPT processes 2.5 billion prompts daily.

They have 700 million weekly users. They're valued at $300 billion. When you've already achieved that kind of ubiquity, you don't need to convince people that AI is transformative. You need to convince them to use your AI for everything.

The strategy is the Google model. Be so ubiquitous you become the verb. When people say ‘just ChatGPT it,’ you've won. But here's where it falls apart: When research firm System1 tested the ads with consumers, only 59% of viewers could identify what was actually being advertised. The logo appears too late. The distinctive assets are barely there. The ad is so generic that it could be selling any AI tool; swap the logo at the end, and it works just as well for Gemini, Copilot, or whatever new option launches next week.

That's the fundamental problem. Most people already can't tell AI providers apart. When distinctiveness matters most, ChatGPT created ads that disappear into the background.

Claude: celebrating your problems

Claude's campaign opens with a voiceover: "There's never been a worse time." Images of problems flash across the screen. Then it flips. "There's never been a better time to have a problem."

The timing was deliberate. Just months earlier, OpenAI had launched Sora, its text-to-video tool. Suddenly, anyone could generate video content at scale. The result was a flood of low-effort, algorithm-chasing slop. Anthropic saw its opening. While everyone else celebrated automation, they positioned hard against it. Their "Keep Thinking" campaign became explicitly anti-slop, against AI-generated garbage, and for actual human thinking.

The emotion they're selling is transformative ambition. AI as a thinking partner for your most meaningful challenges, not a shortcut past them. And then they took it off the screen and into the real world.

Claude ran a café pop-up in New York. Over 5,000 people visited across a single weekend. One founder drove ten hours from Ohio just to experience it. The main draw was the Baseball caps embroidered with a single word. Thinking.

They sold out immediately. But the genius wasn't the cap itself. It was what wearing it signals. You've seen corporate swag before, logo-plastered shirts that go straight to the back of the drawer. This was different. The cap doesn't broadcast Claude. It broadcasts you. When someone sees that hat, they're not thinking about AI tools.

They're thinking the wearer is someone who cares about depth over speed. Someone who builds real things instead of churning out clop. Someone solving bigger problems.

That's why people drove ten hours and waited in lines around the block. The cap is a badge that says, ‘I'm one of you.’

Two completely different bets

Both companies needed to address the same mass-market anxiety of AI replacing humans. They took opposite approaches. ChatGPT's bet is to win the everyday productivity category. Be the AI everyone uses for routine tasks. Build a moat through ubiquity and habit.

It's the Google model, be so omnipresent that you become the default. Show regular people achieving small wins like cooking meals, planning trips, and hitting fitness goals. If AI helps you cook dinner, it's not scary. It's just helpful.

The tradeoff is that you end up positioning AI as a ‘nice to have’ rather than something transformative.

Claude's bet is to win the serious work category. Be the AI that ambitious people identify with. Build a moat through tribal identity and aspiration. It's the Apple model; premium positioning through meaning.

You don't need everyone. You just need the people who define themselves by their work to see you as essential.

Not coincidentally, "Keep Thinking" draws an obvious comparison to Apple's own "Think Different" campaign. The echoes are intentional, and they highlight the real indicator of who will win this battle. Apple has not come to the table with its own AI products. So while OpenAI is directly challenging Google (not exactly a company I’d bet against…) Anthropic can wander in and claim a gaping void of uncontested opportunity in the market.

Claude has 16–19 million monthly users. Much smaller scale than ChatGPT, but look at how those users engage. 36% is coding, 77% of enterprise usage is automation, and 70–75% of revenue comes from high-value API calls. Tellingly, while ChatGPT has more direct users than Claude, Anthropic has overtaken OpenAI in enterprise API usage.

Source: Menlo Ventures.

When you can't compete on scale, you compete on intensity. You build strong believers rather than accumulating passive users.

Why Claude wins

I won’t drag out a reveal of my take on this. Claude's campaign is objectively better. Not just emotionally, but strategically and creatively. System1's research found ChatGPT's ads scored in the lowest quintile for both long-term brand growth and short-term sales impact.

Every element of Claude's campaign is distinctive from frame one. You know it's Claude before you see their name, not because of logo placement, but because the entire aesthetic, message, and positioning is unmistakably theirs.

That distinction matters enormously right now. Research from Menlo Ventures found that most consumers genuinely can't tell AI providers apart; they see ChatGPT, Claude, Gemini, and Copilot as interchangeable. Technical capabilities have reached rough parity. For most people, the differences are marginal at best.

When everything looks like a grey AI bucket, distinctive brand assets are the only thing that makes you immediately recognizable.

ChatGPT's pull-up ad could be selling any tool. Slap a Gemini logo at the end instead of OpenAI’s, and it still works exactly the same. Claude's "Keep Thinking" campaign couldn't belong to anyone else. The anti-slop positioning. The thinking caps. The café pop-up. The entire aesthetic. You'd recognize it as Claude without the logo. That's the difference between making ads and building a brand.

ChatGPT builds a transactional relationship of ‘I use this to get things done,’ and Claude builds a transformational one around ‘this changes what I'm capable of.’ ChatGPT says, ‘We make things easy by thinking for you,’ and Claude says, ‘We help you think bigger.’

With OpenAI now rolling out ads in ChatGPT, Anthropic ran a campaign mocking the ChatGPT pull-up ad. I have no words… just watch it.

Playbook / how you can apply this

Hopefully, you've spotted a few things in these two campaigns that apply to your own brand building. Here are five takeaways worth acting on.

• Pick a lane and own it completely: Don't try to be everything to everyone. ChatGPT's biggest mistake was making an ad so generic it could belong to anyone. Define a specific position, whether that's everyday utility or serious work, and build every brand asset around it without compromise.

• Sell identity, not features: People don't buy products, they buy what those products say about them. The thinking cap sold out not because it said "Claude" but because it said something about the person wearing it. Ask yourself: what does choosing your brand signal to the world about your customer?

• Build distinctive assets from day one: A logo is not a brand. Color, tone, aesthetic, positioning, these are the things that make you recognizable before your name appears. If you swapped your logo onto a competitor's ad and it still worked, you don't have a brand yet.

• Take your brand off the screen: The café pop-up that drew 5,000 people over a weekend wasn't a marketing stunt; it was proof of concept for a community. Find ways to make your brand tangible and physical. The brands people remember are the ones they've actually experienced.

• When you can't compete on scale, compete on intensity: Claude has a fraction of ChatGPT's users, but their users are deeply engaged, high-value, and tribal. A smaller audience that genuinely believes in what you stand for is worth more than a massive audience that barely notices you.

I’ve covered all these themes and more in my weekly newsletter, Brand Chemistry. If you’re thinking about brand and how you come across to your audience, definitely check it out!

Future

The AI category is about to get significantly more crowded. Google, Meta, and a dozen well-funded startups are all racing toward capability parity. Within a few years (possibly sooner), the technical differences between models will be negligible for most use cases. At that point, the only thing separating one AI product from another will be brand.

That's the window we're in right now. The companies placing serious bets on brand building today are buying themselves an asymmetric advantage that will compound over time. Claude's tribal identity, distinctive aesthetics, and anti-slop positioning are way more than just clever marketing; they're infrastructure for long-term defensibility.

The parallel to other maturing categories is hard to ignore. When smartphones reached capability parity, Apple didn't win on specs. When coffee became commoditized, Starbucks didn't win on beans. When social media fragmented, the platforms that survived built genuine cultural identity around their product.

AI is on the same trajectory. The benchmark era is ending. The brand era is just beginning. The companies that figure out how to make people feel something will own this category for the next decade. And right now, Claude is doing that a lot better than ChatGPT.

Extra reading / learning

• Sam Altman + OpenAI = The Future We Will All Live In - February, 2024

• Helping Companies Become AI-First - October, 2025

• You GEO Questions Answered - January, 2026

And that’s it! You can connect with Isaac on LinkedIn here, subscribe to Brand Chemistry here, and work with Pistachio here.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

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beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 2,341 new legends who joined this week! You are now part of a 266,664 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

🧠 Inference Engineering, Open Models & Shipping AI At Scale. An interview with Philip Kiely, Head of Developer Relations at Baseten.
🧱 LinkedIn Just Voluntarily Tanked Their Algorithm (+ How To Win). We get down and dirty on the tactics to build your brand.
🥄 Neighbors Feeding Neighbors, At Scale. An interview with Joey Grassia, Co-Founder & CEO at Shef.

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HOUSEKEEPING 📨

Did you know there is a way to link your Twitter so you can have a big, fat pop-up for people to subscribe? I learned this, just this month. For example, my unique link is https://twitter.com/intent/user?screen_name=bill_kerrrrr. If you use the first half of the link and finish with your handle, where I have ‘bill_kerrrrr’, you can do it yourself. I am telling you this 1) because it’s cool and 2) because I have literally no followers on Twitter, so go follow me!

Also, this is another great piece from the cutting room floor of our recent Tracksuit zero-to-one. I love these pieces. And they are just too good not to share. I actually had to cut one full interview from this, so we may use that in the future, too. Anyway, I hope you enjoy it!

ZERO TO ONE 🌱

Connor Archbold, CEO & Co-Founder at Tracksuit

Connor Archbold is the Co-Founder and Co-CEO of Tracksuit. Before building the company, he spent time across corporate law, fundraising, and early-stage startups, experiences that shaped how he thinks about scale, incentives, and building durable businesses.

At Tracksuit, Connor has been instrumental in taking the product from a local New Zealand launch to a global brand tracking platform, with a sharp focus on culture, long-term thinking, and doing brand properly in a performance-obsessed world.

Connor Archbold.

Why are you and Matt well-suited to build this product?

Matt and I come from very different backgrounds, which ended up being a real strength. Matt helped launch Uber in New Zealand, while I started out as a corporate lawyer. After that, I ran a surfing and yoga retreat in Nicaragua for a year with my now wife, and later launched New Zealand’s first accelerator program in Auckland. I’ve taken a pretty non-linear path, and that gave me a broad perspective on how businesses actually work.

What really brought us together was a shared first-principles approach to brand tracking. We kept asking basic questions that no one in the market seemed to challenge: why isn’t brand tracking standardized, why don’t market research firms share benchmarks, and why is brand data still delivered as a managed service in hundred-page slide decks six weeks after the research is done? How is a modern marketer supposed to make decisions with data that old. Those questions formed our initial hypothesis. We then partnered with James Hurman, one of the world’s most respected brand strategists, and the team at TRA, a highly regarded market research agency.

Couldn't think of a better compliment.

Combining Matt’s and my first-principles thinking with their deep brand strategy and research expertise allowed us to create the first version of Tracksuit in a way that challenged the status quo from day one.

What has changed most since the first days?

In the very beginning, the product was actually called Daylight, not Tracksuit. The idea was that we were ‘bringing brand data into the daylight.’ The branding was completely different, too: it was blue and yellow instead of purple and green. In hindsight, we were taking ourselves a bit too seriously back then.

Changing the name to Tracksuit was a big moment. It fit our personalities much better and reflected how we wanted to show up in the world. It was lighter, more approachable, and more aligned with the counter-positioning we were aiming for. The name Tracksuit came from how we wanted to position ourselves against traditional market research firms. They’re the suits, we’re the tracksuits. We’re built for speed and comfort, and everything we did early on was intentionally counter to the slow, heavyweight, ‘dinosaur’ market research model. It also helped that the word ‘track’ is literally in the name, and we do brand tracking. We wanted something fun, memorable, and a little bit cheeky. From the start, we were thinking about how the brand could be engaging beyond just the product; things like doing an annual ‘Tracksuit drop’ with a fashion brand and leaning into that flywheel of creativity.

Also, what's better than working in Tracksuits?

One of my favorite early memories is our second employee, Mikayla, turning up on her first day, probably expecting a slick startup experience. Instead, we were packing gray Tracksuit sweatsets into bags and personally delivering them to our first 50 customers around Auckland. I even ran out of petrol at one point. It was completely unglamorous, but it perfectly captured what the name Tracksuit was all about.

Were there any major product changes from v1 to the product today?

Yes, the product has changed a lot. In fact, at the very beginning, there was no product at all. We started with a hypothesis about what was broken in the brand tracking and market research industry. Matt mocked up what a good dashboard could look like using a simple slide deck, and we worked out the rough economics, like the cost of running surveys and what we might be able to charge. The first version was very scrappy. We ran the surveys ourselves and pushed the data into a white-label data visualization tool, essentially a Power BI setup. We launched in quarterly cohorts, which gave us the ability to completely rebuild the product every three months. We’d launch a cohort, learn from their experience, rebuild, and then bring in the next group. Within nine months, we had around 75 customers and roughly $1 million in ARR across three cohorts.

Source: Tracksuit.

As the product matured, it evolved from ‘nice dashboards’ into something much more insight-driven. Instead of expecting marketers to dig through charts, the focus shifted to helping them quickly understand what the data is telling them and why it matters. From there, we’ve continued moving toward more natural ways of interacting with data: asking questions, surfacing insights, and supporting strategic decision-making rather than just presenting raw metrics.

How did you validate the idea before building the product?

We validated the idea entirely through conversations before building anything. At the start, there was no product. Just a clear hypothesis about what was broken in brand tracking and how it could be done better. We listed around 100 marketers and agency people who regularly interacted with brand tracking and started talking to them one by one.

We were very strict about validation. We told ourselves we wouldn’t build the product unless we could get at least 10 people to commit in advance and effectively sign on as beta customers. In the first 20 conversations, people were polite but non-committal, so we kept refining how we explained the problem and the solution. By the 68th conversation, we had our 11th customer sign up for a full year of brand tracking. Only then did we build anything. We delivered the first version within 30 days, launched those customers as a cohort, and learned directly from how they used it. That customer-led approach shaped everything (from the product itself to how we priced it), and it set the foundation for how Tracksuit has been built ever since.

At what point did you move from low-code, no-code tools to a fully in-house platform?

We ran three quarterly cohorts using low-code tools before moving fully in-house. In those early days, the product was essentially a white-label data visualization setup—Power BI being the main example—with the right design and structure, but not our own native app. Around the 12-month mark, we brought the product team in-house and finished building our own platform.

By that point, we’d already rebuilt the product multiple times through those early cohorts, so moving in-house was more about taking ownership and polishing what we’d learned rather than starting from scratch.

We’re now several versions beyond that initial build, but the core experience still looks and feels surprisingly similar to today’s Tracksuit.

Who were the first employees, and why did you choose them?

Our first two employees were Hamish and Mikayla, who both joined in the same month. They were employees one and two, and we hired them very intentionally. Hamish fits what I think of as a ‘unicorn’ profile. He had recently been selling himself and had only fairly recently stepped into a sales manager role, so he was still very close to the work while also learning how to lead a team. He was also returning to New Zealand from the U.K. during COVID, which worked in our favor. That period brought a lot of high-quality talent back home, and we were able to take advantage of that timing. Mikayla came from a different angle. She was a CMO at a consumer brand and had tried to bring Tracksuit into her own boardroom.

When that didn’t work out, it actually became a moment of clarity for her: if Tracksuit existed to give CMOs credibility in the boardroom, and she couldn’t get it adopted internally, then maybe she should be building it instead. That insight opened the door to a conversation about her joining the company.

Working with swag.

She initially joined across customer and marketing, working closely with me on customer success while also shaping our early marketing. Over time, she took full ownership of marketing and eventually moved to New York. Hamish has since grown into our CRO. Both have scaled their roles significantly alongside the company, which has been incredibly rewarding to see.

What was the best thing you did in the early stages?

The best thing we did was hiring. We hired our first employees at the end of 2021. That’s when Hamish and Mikayla joined the company as employees one and two, right at the early zero-to-one stage. Matt and I couldn’t have built Tracksuit on our own, and the people we brought in early are what really made the company what it is today. Seeing those same people grow from a bootstrapped, pre-seed stage all the way through to Series B—often staying in the same leadership seats—is pretty rare, and it’s something I’m incredibly grateful for. That kind of growth is hard, and all the credit goes to them.

You wish your team was this cool.

Bootstrapping also forced a level of focus that helped us immensely. Bootstrapping can go two ways: you either chase any revenue you can find and accidentally become a services business, or you stay disciplined. We chose the second path. We committed to a clear hypothesis, only did the thing we believed in, and kept iterating on that one idea. That maniacal focus, combined with strong early hiring and the timing advantage of great people returning to New Zealand during COVID, played a huge role in Tracksuit’s early success.

How do you think about team structure and geography as you scale?

We’re an in-office company, and that’s a deliberate cultural choice rather than a productivity one. Matt and I genuinely enjoy being in the office with people, and we think it really helps with idea sharing and cross-pollination, especially in the early stages. So instead of being fully remote, we’ve opened offices intentionally when it made sense for the business.

We started in Auckland, where most of our product and engineering team is still based. From there, we opened Sydney. I then moved to New York for four months with my family to launch the U.S. office, and Matt went to London to open the U.K. office. In each case, we made sure the founders were physically there to hire the first group of people and set the tone.

A big part of that strategy was seeding new offices with ‘culture carriers’ from the early days. We brought over people who naturally embodied Tracksuit’s values and way of working, then hired locally around them. That approach helped each new office feel like a true extension of the company, rather than a disconnected satellite team.

What do you mean by ‘culture carriers,’ and why are they important?

A culture carrier is someone who embodies the company’s values without having to think about it. It just comes naturally to them. Early on, when it was just the four of us—Matt, Mikayla, Hamish, and me—we sat down and wrote out everything that would inevitably come out of our personalities if we built a billion-dollar business together. The good, the bad, and everything in between, because building something like that is hard and you experience all of it.

You can't fake this.

From that exercise, we distilled things down into about six core values, which became Tracksuit’s values. Over time, you realize that most people align with those values to some degree, but some people live them so naturally that it feels effortless. Those are culture carriers. They’re important because culture scales through people, not documents. When you bring culture carriers into new teams or new offices, they set the standard by how they behave, make decisions, and work with others. That’s far more powerful than trying to enforce values top-down, especially as the company grows.

How did you seed new offices with these culture carriers?

When we opened new offices, we made a point of physically being there as founders and surrounding ourselves with culture carriers from the early team. In New York, for example, I moved over for several months to launch the office, and Matt did the same in London. That hands-on presence helped us set the tone from day one.

Alongside that, we invited people from the existing team to move overseas and help establish those offices. It wasn’t forced; people raised their hands when they were ready. Someone like Mikayla was excited about the opportunity to live in New York, so she moved over and helped embed the culture. Over the first year of each office, a small group of culture carriers relocated, and then we hired locally around them.

That approach ensured the new offices didn’t feel disconnected. They inherited the same values, behaviors, and energy as the original team, which made scaling across geographies feel much more cohesive.

What was the most stressful period so far?

The most stressful periods came from bootstrapping while growing very quickly. We were hiring ahead of revenue, closing lots of deals, but invoices don’t always get paid on time. There were a couple of moments where Matt and I were staring down payroll with almost nothing in the bank, despite having hundreds of thousands in receivables that simply hadn’t landed yet.

In one of those situations, we ended up taking what I’d call a very ‘spicy’ loan, not something I’d generally recommend. Our credit cards were maxed out, there was no cash available, and we needed to make payroll that week. It worked out in the end because the receivables came through shortly after, but those were definitely nights where we lost a lot of sleep.

Product-wise, expanding into the U.S. was also harder than expected. Tracksuit was initially built for the New Zealand market, which is relatively simple. When we launched in the US, marketers cared deeply about regional tracking (cities like Seattle or entire states like Texas), and we didn’t support that at first. Product–market fit in the U.S. took real effort until we made significant changes. To manage that risk, we treated every new region and product launch as its own bootstrap: it had to be cashflow positive on its own, even after we’d raised capital.

Why raise capital instead of continuing to bootstrap?

We decided to raise capital primarily to bring in great partners and give ourselves more breathing room for the next stage of growth. Matt and I hadn’t built a company at that scale before, so having investors who had been there and could add real value, not just money, was important to us. Being part of those communities and learning from people with more experience helped us think differently about what came next.

It also meant we didn’t have to keep putting ourselves in situations where we were relying on ‘spicy’ loans to make payroll. While we probably could have continued bootstrapping and even raised more than we did, we were intentional about raising a reasonable amount relative to our growth. That gave us comfort and the ability to take some calculated bets without constantly stressing about cash.

Matthew Herbert, Co-Founder & CCO at Tracksuit

Matthew is the co-founder and Chief Commercial Officer of Tracksuit, the brand tracking platform built for modern growth teams. Before starting Tracksuit, he helped launch Uber in New Zealand and later worked at Mish Guru, advising global brands on how to reach younger audiences through emerging platforms.

Matt and Connor.

At Tracksuit, he brings that operating mindset to brand measurement, focused on making it practical, accessible, and actually useful day to day. His work sits at the intersection of growth, brand, and data, helping teams understand what’s really driving long-term demand, not just short-term clicks.

What is the initial idea behind Tracksuit?

The initial idea came from looking at how modern businesses were growing and realizing marketing had become almost entirely performance-driven. For the past decade or so, teams poured money into channels like Meta and Google because the returns were easy to measure. Put a dollar in, get three back. Finance teams, investors, and marketers could all understand it. But over time, those returns started to decline. Brands hit a ceiling once they’d exhausted existing demand.

Source: Tracksuit.

Source: Tracksuit.

Source: Tracksuit.

What we saw was that marketing really has two jobs: harvesting existing demand and creating future demand. Performance marketing is great at first, but brand marketing is what brings new people into the category and builds familiarity over time. The challenge was that brand measurement was expensive, slow, and mostly reserved for the biggest companies in the world, paying large research consultancies. So the core idea behind Tracksuit was to make brand tracking accessible, affordable, and understandable for modern growth-stage businesses, and to put brand back on the agenda alongside performance metrics.

In the early days, we focused on stripping brand tracking back to what actually mattered. We spoke to dozens of CMOs and marketing leaders and found they mostly relied on a small set of core insights: category size, brand awareness, brand perceptions, and competitor benchmarks. We built the first version of the product around those fundamentals, validated demand by securing upfront subscriptions from early customers, and used that to build the initial platform. Since then, Tracksuit has evolved into an always-on, easy-to-use brand tracking tool that sits alongside other business metrics and helps teams make faster, more informed decisions as they grow.

What unique insight does Tracksuit deliver that platforms like Meta can’t?

Platforms like Meta are great at showing what’s happening within their own ecosystems, but they only tell part of the story. What Tracksuit delivers is an independent, category-level view of brand performance—the kind of insight that has traditionally only been available to the world’s largest companies through expensive research consultancies.

We looked at how enterprise brands use tools from providers like Kantar or Nielsen and saw that, in practice, most teams rely on a small set of core insights: how big the category is, how well the brand is known, what people think and feel about it, and how it compares to competitors. Tracksuit takes those fundamentals and makes them accessible, affordable, and always on.

Instead of one-off reports or channel-specific metrics, teams get a live view of brand health across the entire market, which they can use to guide strategy, investment, and long-term growth decisions.

What are the biggest product benefits you saw early on, beyond cost reduction?

Beyond cost, the biggest early benefit was simplicity and accessibility. From the start, Tracksuit was designed to create a common language around brand, so marketers, executives, finance teams, and investors could all understand what was happening without it turning into marketing jargon or a black box. The goal was to strip brand measurement back to its essentials and make it easy for everyone in the business to see where the brand stood and where it needed to go.

The other major benefit was being always on. Most businesses only measured brand once or twice a year, which meant they were making decisions based on outdated information. Tracksuit gave teams a live, up-to-date view of their category, competitors, and brand performance.

That speed to insight meant brand data could actually be used in board meetings, agency reviews, and strategy decisions, rather than sitting in a report from months earlier.

Why did you decide on a co-leadership structure, and how did your role evolve?

Things moved very quickly in the early days. We set an initial goal of reaching one million in recurring revenue in about 18 months, and we hit that in nine. As the business scaled, Connor and I were very intentional about leaning into our respective strengths and working as a joint force, which naturally led to a co-CEO structure. I focused more on growth, while Connor focused on operations and customers, and having two people sharing that responsibility made it easier to move fast and make better decisions.

As the company grew further and we began preparing for international expansion and raising capital, our roles started to diverge. Connor spent more time leading fundraising and investor relationships, while I stayed closer to the day-to-day business. When I moved to the U.K. to help launch our U.S. and U.K. operations, my role evolved into Chief Commercial Officer. That shift allowed me to focus on strategic partnerships and ensuring our brand data and insights were embedded into the tools and workflows marketers, strategists, and investors already use, while we continued to review and adjust the leadership structure as the business scaled.

What was the most successful thing you did in the zero-to-one stage?

Three things made the biggest difference in the zero-to-one stage. First, we got very clear on why we were building the business. Early on, we brought the core team into a room and aligned on what success meant, both tangibly and intangibly. That clarity gave us a shared reference point for decision-making as we grew and helped people understand how their work contributed to where we were going.

Second, we defined our core values early. We treated the company as a blank canvas and were deliberate about the culture we wanted to build. Those values became the foundation for how we hired, rewarded people, and held ourselves accountable, and they’ve stayed consistent as the team has grown.

Source: Tracksuit.

Third, we spoke to the market constantly. We made the number of conversations we were having with customers, advisors, and partners a key metric. That ongoing feedback helped us validate ideas early, avoid building in a vacuum, and stay tightly aligned with what the market actually needed.

The exercise helped us find common ground across what people wanted, both personally and professionally. On the intangible side, we aligned on wanting to make a meaningful, long-term impact on how businesses grow by connecting a strong brand strategy with better business outcomes. We also cared deeply about building a team and a place of work people were genuinely proud of, where they felt like ambassadors for what we were building.

Celebrating, the tracksuit way.

On the tangible side, we set clear early goalposts. We wanted to build a globally recognized technology company out of Australia and New Zealand, create opportunities for local talent, and prove we could scale through the difficult early stages of growth. We aligned on getting to around ten million in recurring revenue, serving a thousand customers, and building a business with real long-term value. That shared clarity gave us direction and helped guide decisions as the company evolved.

What has been the most difficult period in the company’s journey so far?

One of the toughest moments came about 18 months in, when we had a team of around 15 people and came very close to not making payroll. Cash was tight, company cards were maxed out, and the responsibility of supporting the team weighed heavily. We ultimately bridged the gap with a short-term loan while outstanding invoices were paid, but at the time, it was extremely stressful.

Beyond that, staying focused has been an ongoing challenge. There are constant temptations to chase bigger contracts or expand into adjacent areas, especially in a broad industry like market research. We made a deliberate decision to stay narrowly focused on brand tracking and do it better than anyone else.

International expansion has also been difficult, particularly managing teams across multiple time zones. Aligning communication, context, and cadence across regions remains one of the hardest parts of scaling the business.

Was raising capital tied to the cash-flow stress?

No, raising capital wasn’t driven by cash-flow stress. At the time, we had customers, revenue, and invoices out; the issue was timing, not the fundamentals of the business. We were very intentional about building a sustainable, bootstrapped company from the start.

A pack of happy tracksuiters.

When we did raise capital, it was about fueling the next phase of growth rather than staying alive. Coming out of the pandemic, investors were focused on profitability and strong fundamentals, which played to our strengths. Raising allowed us to invest in product, go-to-market, and international expansion, and to bring on partners who could add credibility and help us scale. Timing in the market and the growing focus on brand also worked in our favor.

How were you personally feeling during that period?

The period around the cash-flow stress was intense, but relatively short. It was stressful seeing accounts and credit cards stretched, but we knew we had customers, revenue, and a clear path out of it, so that pressure didn’t drag on for long. The heavier personal toll came later. After several years with the foot on the accelerator, moving from Auckland to London, getting married, managing multiple markets, constant travel, and working across time zones, it caught up with me. I hit burnout hard and fast in early 2024 and had to take time off because I wasn’t looking after myself. It was a real wake-up call. It wasn’t easy to go through, but it forced me to step back, reset, and make changes before things got worse.

Mikayla Hopkins, Head of Marketing at Tracksuit

Mik joined Tracksuit in late 2021 as one of the very first team members and helped shape its early strategy, culture, and global growth trajectory. Under her leadership, the marketing team has expanded significantly while maintaining a focus on blending B2B utility with the energy and creativity more typical of consumer brands.

Mik.

Her career path includes multiple industries and roles, giving her a unique perspective on brand building. Mik started in a big beer company and then moved into beauty as CMO of The Face Place, a luxury cosmedicine business. Today, at Tracksuit, Mikayla champions a marketing philosophy that balances short-term demand conversion with long-term brand building, arguing that both are essential to sustainable growth. Her voice also extends into industry conversations on the evolving role of creativity and brand leadership in the modern marketing landscape.

When and why did you join Tracksuit?

I joined Tracksuit as employee number four, after the two co-founders and our Head of Sales, back in 2021. I joined early on because I was personally experiencing the problem that Tracksuit set out to solve. My background is deep in the world of brand. Over time, I noticed that when I was having conversations with the board, my seat at the table was getting smaller and smaller because I couldn’t confidently articulate the power of brand.

I had a group of girlfriends who were all brilliant marketers, and we met for coffee every month. One day, someone in that group said, “Guys, you have to hear about Tracksuit.” It wasn’t even what she was saying; it was how she was saying it. There was such deep enthusiasm. I remember thinking, ‘we’re just talking about software. Why is she so excited? Nobody talks about SaaS like this.’ She said it was finally a way for marketers to prove their value without spending $200k+. That got me really, really excited.

Two legends.

At that point, Tracksuit had seven customers. It had just been Matt and Connor swinging wireframes and selling the dream. They were at about $100k ARR, roughly six months into the journey. Now we’re at $42 million ARR, and I’ve been with the crew since day one.

What role did you play early on?

At Tracksuit, we believe marketers have two jobs. The first is to harvest demand in the short term with conversion activity. The second is to build future demand for the brand among a much wider group of people who haven’t even entered the category yet. Both jobs are equally important. But digital analytics have only ever told us how we’re doing with the short-term conversion piece. Companies fail time and time again because they over-exhaust that small group of people who are ready to buy right now. The challenge is that analytics only tell us how well we’re doing in the short term. They don’t tell us how we’re building future demand or how we’re actually building the commercial engine. I came into Tracksuit to link that theory with the product.

Top of the world.

In the beginning, I was leading both Customer Success and Marketing. My job was to understand the pains, fears, and dreams of our customers and figure out how to tell the commercial story of Tracksuit and brand building at large. Day to day, that meant everything: product development, doing demos, building out positioning, running events; basically the full gamut of a generalist who could look after CS and marketing.

My role today is very, very different. We now have a marketing team of 20, with people across New Zealand, Australia, the US, and the UK. My job has shifted from being the person on the ground doing everything to leading leaders and scaling a global team.

What was the single most important thing you did in the zero-to-one?

One of the best things we did was show up differently in the market. B2B is usually stodgy and boring. It’s not playful. We didn’t want to be that. We wanted to be a B2B brand that walked and talked like a consumer brand. A really effective example of that was the tracksuits, the actual apparel.

Yes, our company was called ‘Tracksuit,’ and we sold a technical dashboard, but we wanted to show up in a way that felt built for speed and comfort. And what better way to do that than with real tracksuits? When it was just the four of us, we were literally driving around town dropping them off to early customers and supporters. Those customers would post photos of themselves wearing the tracksuits on LinkedIn. It was amazing. People started fighting over them. Everyone wanted a piece of the merch. It created this real community moment where people felt: they’ve got a great product, and I want to be part of this. It was a really effective way for us to stand out in the noise early on.

Love, Tracksuit.

What was something that bombed in the early years?

Looking back on the last four years, it was definitely a challenging ride, but we also had a lot of wins behind us. In some ways, we became a bit of a unicorn overnight. And when you’re in that position, so much gets handed to you on a silver platter. The challenge with that is that it becomes really hard to know explicitly what you need to focus on.

We had moments where we got excited by lots of different opportunities. There was this path over here, another path over there, and we didn’t always know which one to prioritize. We’ve had to get much better at saying no to 99.9% of opportunities instead of getting shiny object syndrome and chasing everything. You can realistically go out and do anything, but if you try to be everything to everyone, you end up being nobody. Where we could have moved even faster was by getting stronger earlier at flexing that ‘no’ muscle.

What did the go-to-market look like in the very beginning?

In the first year, we measured success by the number of conversations we were having. Our entire go-to-market motion was go out and speak to every single person who we believed had this problem: not being able to build, communicate, and measure the impact of their brand marketing. We were constantly asking: “Are we starting to see patterns in the pain points? Is the solution we’ve created actually matching those problems?” That helped us refine our positioning really early on. When you’re moving people from problem-aware to solution-aware to product-aware, we had a very clear idea because we had had so many conversations about exactly what we needed to say and what promise we needed to make to bring people in the door.

Mik drop.

Those initial conversations were a mix of user interviews and actual sales pipeline. We have a very charismatic group of people at Tracksuit, so people were really open to jumping on calls. Even if they hadn’t seen the product, they were happy to talk about their problems. At the same time, once we had customers, onboarding them was very white-glove and hands-on. So we were having frequent conversations on both sides: with prospects who were helping us shape the product, and with real users giving feedback in real time about what made sense and what didn’t. A lot of those early calls were framed as learning conversations and problem discovery rather than formal sales meetings. The focus was on understanding what hurt and what they were trying to achieve, more than trying to push a product.

How did that go-to-market evolve once you raised money and started scaling?

As you can imagine, with a team of 200 across the world now, our GTM motion is a lot more sophisticated. We have a strong group of AEs, SDRs, and a really great inbound motion. A big part of it today is telling stories with our data—finding great proof points, case studies, and heroes who believe in the product and getting them to tell our story for us.

Something else that was really effective in year one was building out a flagship event series called Building Brands of the Future. We wanted to be elite but not elitist, so we would hand-pick the people we wanted in the room. Those people would go on to tell our story for us. They would post on LinkedIn and let their network know they were invited into a room of some of the best brand minds in the country. That helped us very quickly create broad awareness of Tracksuit.

Which channels worked best as you’ve scaled? And which have been hard to crack?

In that first year, we didn’t really have a marketing budget, so everything was focused on how we could tell great stories organically. The channel that had the best channel-message fit was LinkedIn. It’s where our customers hang out. It’s where marketers spend their time, honestly, more than Instagram. I know I open LinkedIn 20,000 times a day and probably only open Instagram a couple of times.

We understood that people care about career and social currency. And that was really the crux of Tracksuit. We weren’t just selling brand tracking, we were selling career and social currency. If you use Tracksuit, it makes you a better marketer. That leads to promotions, more marketing budget, bigger teams, more resources, and exponential growth within a company. LinkedIn was the perfect channel to tell those stories. As we expanded, one of the channels that ended up being really effective—but took a lot of experimentation to get right—was our B2B creator network: primarily LinkedIn, and to some extent Instagram.

When it comes to underperformance, the creator strategy is a good example. It eventually became effective, but it was one of the hardest channels to get right. The challenge with creators is that you’re going out to a large volume of people and hoping they have enough ICP overlap with their audience. It’s extremely hard to attribute, and there’s often a lot of bloat in those audiences because creators sometimes grow them in ways that don’t perfectly match your target market.

Early on, we definitely noticed too much wastage when it came to deploying capital into creator partnerships. We’ve refined that now. It’s much more about quality over quantity rather than just going out and seeing who wants to tell our story.

There isn’t one specific channel or campaign I would call a total failure. The bigger challenge was more strategic than tactical. Because things were going well and momentum was strong, we had a lot of exciting opportunities. The risk was saying yes to too many of them at once. The lesson wasn’t that one particular launch bombed. It was that we could have been more disciplined earlier about focus and saying no.

Source.

Can you describe the sales motion today?

Our sales motion is particularly effective because we have very strong AEs who deeply understand the problem we’re trying to solve. More broadly, it’s a really beautiful mix of inbound, outbound, and partnerships. The partnership channel has been a complete game-changer for Tracksuit. Instead of selling one-to-one, we can sell one-to-many. These incredible agencies—usually in the creative space—become our best sellers. They advocate for the work they’re doing, and if an agency has ten customers, all ten can end up using Tracksuit. That channel has been especially important in markets where we don’t yet have as much influence, and we’re very lucky to work with some of the best agencies in the world.

Agencies at the moment honestly deliver about one-third of our revenue at the company. They’re a fantastic channel. We actually have a dedicated partnerships team that holds those relationships and helps those agencies do the best work of their lives, because they have a tool that allows them to demonstrate and communicate what’s happening with brand.

Something we’re finding really interesting is that there will be a time when every single person is using Tracksuit. When that happens, it becomes less about just having the data and more about the ‘so what.’ What are you going to do with that data? How are you going to use it to diagnose and drive strategy? That’s going to be the delta that sets people apart in the agency and creative world.

Have you modeled your go-to-market or partnership strategy on any other companies?

There are definitely strong parallels between Tracksuit and Xero. Initially, when we went out into the world, we weren’t really focused on agencies. Those first ten customers were primarily marketers at CPG and mid-market brands. But then we started to see agencies coming inbound who were really interested in what we were offering.

Tracksuit shows up in a way that is playful and spirited, but underpinned with an incredibly strong intelligence system, and that hadn’t really been done before in ANZ. So product-market fit with agencies happened almost immediately, and that channel has been instrumental to our growth.

There is a slightly different pricing structure for agencies. We do it in a way that allows them either to pass on those cost savings directly to their customers or to absorb it themselves. Most often, they choose to pass it on to the customer, which I think actually shows the deep care of the agency network. There are also additional co-marketing opportunities. If we can tell a compelling story about an agency because they’re doing great work, that enhances the value of Tracksuit for them as well. So it’s not just about price, it’s also about the partnership and visibility that comes with it.

How and why did the geo expansion decisions happen?

Year one was really about building and establishing product-market fit in New Zealand, and leaning on our founder network to make sure that happened with strong momentum. Very quickly, we found that a lot of New Zealand customers were also trying to grow their businesses in Australia; so instead of going cold into Australia, we went directly to our top 20 or 30 customers and asked whether there was appetite for brand tracking there as well. That gave us enough momentum to really go hard into Australia in year two, set up a team and an office.

Source: Tracksuit.

By the end of year two and the start of year three, we were having very similar expansion conversations about both the U.S. and the U.K. One of the challenges we hit was that we originally only tracked brands in a small number of markets. Particularly in Europe, customers didn’t just want U.K. data; they wanted to understand awareness and consideration across many countries. So last year we made a big shift and went from tracking in seven markets to tracking in 27 markets within a couple of months. That created another ramp for us to continue expanding globally.

What core capabilities do you need on the ground to successfully launch a new geography?

We’ve really rinsed and repeated the same setup market after market. What we’ve found is that once there’s enough traction in a region, and you actually need to start servicing customers there, you need a few core pieces in place. You need a Customer Success person on the ground, a Sales person, and ideally, Marketing support. That combination creates the foundation for a go-to-market team that can service, acquire, engage, and drive value for customers. From there, you just build it up over time.

One thing we found particularly in the U.K. is that it can feel like its own little island because of time zones. In those cases, having a strong generalist—almost a GM-type hire—who can own the market end-to-end has been really effective. That’s something we deployed in the early years of the U.K., and it worked really well.

As for reporting, we operate with global functional leadership, so we have a global executive team. I look after the marketing function; we have a CRO who looks after Customer Success, Sales, and Partnerships; we have a Chief Product Officer who looks after product and insights; and we have our CEO who looks after a lot of the operational side. Those functional leaders are responsible for the people in each region.

Local teams report through functional leaders. So the marketer in a region sits within the global marketing org, the salesperson sits within the global sales org, and customer success sits within the global CS org. I really like that global structure. It means you have consistent standards and support across all markets, rather than everyone operating as separate little silos.

Was the tracksuit apparel idea modeled off anything you’d seen from other brands?

Not really. We had a very small budget in the early days, so we asked ourselves: how can we spend this in the most creative, silly way possible that creates some noise? The idea wasn’t copied from another SaaS company. It was more about creating what I call the ‘t-shirt effect.’ I think about brands like Bumble in its early days. People were proud to walk down the street wearing a Bumble t-shirt because it signaled something about them and what they believed in.

I wanted the same thing for Tracksuit. I wanted people to wear their tracksuits and let their world know: I care about building great businesses. It was about giving people a way to flex their career and social currency, and feel like they were part of something important. We didn’t send those tracksuits out explicitly to get UGC. The intention was to create pride and community. The UGC happened as a consequence of that, not as the main objective.

A friend of a dog is a friend of mine.

Extra reading / learning

• Tracksuit’s Bootstrap To Series B - February, 2026

• Throwing out the Mad Men suits and putting on Tracksuits - April, 2024

• Tracksuit’s $25 Million Raise Shows How Brand Metrics Drive Growth - June, 2025

And that's it! You can keep up with Matt, Connor, Mikayla, and Tyson on LinkedIn and check out Tracksuit on their website.

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Attio—powerful, flexible and data-driven, the exact CRM your business needs.

beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 2,383 new legends who joined this week! You are now part of a 264,323 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

🧱 LinkedIn Just Voluntarily Tanked Their Algorithm (+ How To Win). We get down and dirty on the tactics to build your brand.
🥄 Neighbors Feeding Neighbors, At Scale. An interview with Joey Grassia, Co-Founder & CEO at Shef.
💨 Tracksuit’s Bootstrap To Series B. A company that is growing really, really, really fast.

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Part of our vetted LATAM PhD and Masters network, working in U.S.-aligned time zones.

_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

I am lucky enough to be an investor at Blackbird, based out of Australia, and just as I was preparing today’s piece I received news that we (Blackbird) had invested into the Baseten Series E. And now today we are featuring Philip from Baseten. Incredible timing. On the same day, I received news that Blackbird portfolio company, co-founded by a buddy of mine, Charlie, was acquired by Hims & Hers for $1.15 billion.

A great result for the Australian startup ecosystem, and my first meaningful exit with my VC investments. I only somewhat believe in the investment returns of venture capital. It’s more so just super cool to be able to be part of incredible results like this. Now onto today’s piece with Phil from Baseten.

INTERVIEW 🎙️

Philip Kiely, Head of Developer Relations at Baseten

Philip Kiely is a software engineer and leading developer relations expert at Baseten, an AI infrastructure company that helps organizations deploy and scale large-scale generative AI models in production. At Baseten, Kiely focuses on helping teams adopt open-source and custom models, optimize inference performance, and build robust, low-latency systems that power real-world AI products. He also writes and speaks widely on topics like inference engineering, AI model serving, and the practical trade-offs of deploying generative models at scale.

Philip Kiely.

Before joining Baseten in 2022, Kiely worked across software engineering and technical writing at a range of startups, developing a strong foundation in both product development and clear technical communication. He is the author of Inference Engineering and has appeared on industry podcasts and at major conferences to discuss scalable AI systems, model orchestration, and the evolving role of open models in production. Outside of work, he’s a lifelong martial artist, avid reader, and fan of Bay Area sports.

What problem are you working on right now?

I’m working on inference, specifically inference for both open models and custom models. That includes models like Llama, DeepSeek, Flux, Whisper, Orpheus, and others across different modalities, as well as models that companies train themselves and want to build products around.

To explain why inference matters, it helps to start with what inference actually is. If you think about the lifecycle of a generative AI model, there are two phases. First, the model is trained and the weights are learned from data. After that comes inference, which is when you actually run that finished model in production. For people less familiar with AI, I usually explain it like this: if you’ve used ChatGPT, inference is everything that happens between asking a question and getting an answer back.

Inference in a nutshell.

We work with many of the best companies in the industry, from AI-native startups to growing enterprises that are rapidly adopting these technologies. A few years ago, when ChatGPT and Claude were first announced, there were only a handful of companies training frontier models and doing serious inference engineering. In an alternate version of the world, that could have stayed the case, with a few companies owning intelligence and everyone else renting it token by token.

Source: Baseten.

That’s not the world I want to live in, and fortunately, it’s not the world we live in. Today, there are over two million open-source models on Hugging Face that developers can use to actually own the intelligence inside their products. But for that to be possible, those models need infrastructure that allows them to be fast, less expensive, reliable, and easy to scale. That’s what we do at Baseten.

We provide runtime performance optimizations and multi-cloud infrastructure to run inference at scale with state-of-the-art latency, for any open model or any custom model a company creates. We’ve also expanded into training and post-training workflows, pairing fine-tuning and reinforcement learning with inference so teams can build high-quality custom models and gain independence from closed models.

Source.

What’s underestimated when moving from a demo to something customers rely on?

A few years ago, I talked to a lot of people who believed inference wasn’t the hard part. Some very big names in the industry even said they thought training would be the real challenge, because once you had the model, you could just put it on an inference engine, run it on GPUs, and be done. It turns out that’s not how it works.

There’s a huge amount of complexity in running inference beyond just getting the model to work. One major challenge is latency. Many AI applications are real time, and users have expectations that translate into SLAs measured in hundreds of milliseconds. Influencing a trillion-parameter model across eight or more GPUs while hitting a time-to-first-token in that range is an extremely difficult technical problem. That requires deep runtime work, highly optimized inference engines, custom kernels, careful configuration, and techniques like post-training quantization, speculative decoding, and KV cache reuse. Some of those improve tokens per second, others reduce time to first token, but they all matter. Even if you manage to make it fast, that’s only half the problem. Once something is fast and useful, people want to use it at scale.

Source: Baseten.

That introduces an entirely different challenge: replicating this setup across multiple regions and multiple cloud providers to meet demand. The biggest AI-native products today are doing trillions of tokens per month. For companies operating at that scale, a single region or even a single cloud provider isn’t enough. You need both performance engineering and distributed infrastructure to work together seamlessly to deliver consistent, low-latency inference in production.

What does your day-to-day look like?

Honestly, I’m still figuring out what my job is. I’ve been at Baseten for four years, and I’m one of the longest-tenured employees, including the founders. When I joined, we had four customers and basically no revenue. Today, we’re a team of over 150 and a multi-billion-dollar company. Early on, my role was very product-focused because we were just trying to figure out what to build. I spent a lot of time on documentation, explaining how things worked. As we grew and hit our first real revenue milestones, that naturally evolved into a developer relations role. Instead of documenting features, I started documenting problems and real-world use cases that customers were facing.

Today, that role has expanded alongside a much larger marketing organization. There’s demand for conference talks, interviews, technical writing, demos, and content of all kinds. Recently, a big part of my focus has been writing a book called Inference Engineering, which I’m publishing soon.

What’s been consistent throughout is that I’ve always tried to explain what’s happening right now. In an industry that moves this fast, having a clear understanding of the present is incredibly valuable. Only recently have I had the space to think a bit further ahead, maybe weeks or months out, and help position both myself and the company for what’s coming next.

How has moving between building and explaining shaped your products?

I’ve seen a lot of structural changes over the years, which anyone who’s worked at a hypergrowth company will recognize. I’ve seen teams that are now incredibly strategic and staffed with some of the best engineers I’ve ever met start out as hackathon projects. There’s constant movement and reshaping. My role has always been to first tell things the way they are and clearly explain what’s happening right now. In a market that moves this fast, simply understanding the present is extremely valuable, both internally and externally.

Source: Baseten.

Only more recently have I had the opportunity to think a bit about what’s coming next. Now that we’ve caught up with the present, I can start looking ahead. This is an industry where vision matters, but it’s not one where three- or five-year roadmaps make much sense. I’ve started thinking in shorter horizons: a week, a month, a quarter, and occasionally a year out. The focus over the last four years has really been on staying grounded in what’s happening today, how things have changed recently, and what people need to know to do their jobs effectively, whether they’re inference engineers, AI engineers, or people looking into the space from the outside.

How do you see the future of AI right now?

One thing I’m really excited about is the continued momentum around open-source models. A couple of years ago, the common belief was that open models just weren’t good enough compared to closed models, so they weren’t very useful. Then models like DeepSeek v3 and DeepSeek R1 came out and closed that gap.

After that, the conversation shifted to whether open models would keep up, fall behind, or jump into the lead. That’s not the most productive way to look at it though. The real utility of open models isn’t determined by benchmark scores. It’s determined by the capability thresholds they’re able to cross.

If you look at the past, you can see how this plays out. As closed models improved, they crossed invisible thresholds that unlocked entirely new kinds of products. Early models that powered things like customer support agents or code editors weren’t very good. They were slow, expensive, and unreliable, but they crossed just enough of a capability threshold for people to start building on them. When open models crossed those same thresholds weeks or months later, builders were able to switch and benefit from lower costs, better performance, and more control. Looking ahead, I can see frontier applications of closed models today that, in a few months, we’ll be working to make cheaper and faster in the open ecosystem.

Right now, that includes things like reasoning agents, where closed models still have an edge, as well as speech-to-speech systems, video generation, and world modeling. I’m particularly interested in what happens when these systems become twice as fast and ten times cheaper. I also see a big shift toward reinforcement learning. The best teams today are taking high-quality open models and doing deep fine-tuning to push them across capability thresholds faster. Right now, only the leading teams are doing this, but I think within a year it will be standard practice across the industry.

How do you use AI in your day-to-day?

AI has had a much bigger impact on my work life than my personal life. I’m able to ship substantially more today than I could one, two, or three years ago because I’ve really dialed in the tools I use. As an engineer, I use Cursor constantly. It allows me to build one-off or custom software that wouldn’t otherwise be worth the effort. Sometimes I’ll build an entire application during my commute home.

I also use Descript a lot for video and audio editing. I’ve used traditional tools like Final Cut Pro, so I know how long even basic editing can take. With Descript, I can film, script, edit, and publish a video about a new model within a couple of hours because the editing process is so fast. We’ve also adopted a lot of Notion’s new AI features internally, which have been great. I use AI extensively in writing and proofreading, especially while working on my book. I’m also using AI-generated voice tools to produce the audiobook version.

One tool that’s especially important for me is Whisper. I don’t type particularly fast, so being able to speak and have text appear accurately is incredibly helpful for someone whose job revolves around creating content. At this point, AI tools are so ingrained in my workflow that I often forget I’m using them until I stop and list everything out.

Is there anything I should have asked you?

The main thing I’d emphasize is just how early we still are in inference engineering. There’s going to be a massive increase in demand for inference engineers over the next year, and this is where I’ve personally bet the foundation of my career.

As more companies adopt open models, they’ll all need people who understand how to serve and operate these systems. Even companies that don’t build inference platforms in-house still need teams that know how to run and manage them effectively. There’s growing demand not just for engineers, but also for executives who understand inference, people who know how to sell it, and people who know how to manage it. That’s why I wrote Inference Engineering. It’s a 300-page book that captures everything I’ve learned over the last four years at Baseten.

Inference Engineering.

The goal is to give people a clear roadmap to becoming experts in inference, which I believe is one of the most valuable areas in AI right now.

Extra reading / learning

• Arctic Vaults, AI Agents & The Future Of Dev Tools - June, 2025

• Launching Athyna Intelligence - January, 2026

• Why AI Is Easy To Demo But Hard To Trust - February, 2025

And that’s it! You can follow Philip on LinkedIn or check out Baseten on their website to keep up with what they’re building!

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

Source.

Source.

Source.

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Thesys*—a Generative UI company that helps anyone build AI apps and agents that respond with interactive UI like charts, forms, cards, tables, and more, instead of walls of text.

beehiiv: We use beehiiv to send all of our newsletters. Apollo: We use Apollo to automate a large part of our 1.2M weekly outbound emails. Taplio: We use Taplio to grow and manage my online presence.

See the full set of tools we use inside of Athyna & Open Source CEO here.

HOW I CAN HELP 🥳

P.S. Want to work together?

1. Hiring global talent: If you’re hiring tech, business or ops talent and want to do it 80% less, check out my startup, Athyna. 🌏

2. See my tech stack: Find our suite of tools & resources for both this newsletter and Athyna here. 🧰 

3. Reach an audience of tech leaders: Advertise with us if you want to get in front of founders, investors and leaders in tech. 👀 

That’s it from me. See you next week, Doc 🫡  P.P.S. Let’s connect on LinkedIn and Twitter.

👋 Howdy to the 2,438 new legends who joined this week! You are now part of a 261,940 strong tribe outperforming the competition together.

LATEST POSTS 📚

If you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.

🥄 Neighbors Feeding Neighbors, At Scale. An interview with Joey Grassia, Co-Founder & CEO at Shef.
💨 Tracksuit’s Bootstrap To Series B. A company that is growing really, really, really fast.
🗣️ Unfiltered: Hyperbound From The Inside. The conversations that shaped the company.

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_{Interested in sponsoring these emails? See our partnership options here.}

HOUSEKEEPING 📨

I turned 40 years young recently. And right as I did, I began to notice more and more grey hairs through my beard. What started as a few little white hairs on my chin is spreading like wildfire. First, the random few stranglers on the chin have been joined by countless more, while also beginning to migrate to new lands across the side of my jaw.

But you know what? I kinda like it. I am open to the salt-and-pepper beard look. It’s one of the multitude of ways I am aging—not as ripped, teeth going crooked, wrinkles showing up—that I actually welcome. Aging is a funny thing. I believe it’s like the famous Hemingway line, “How did you go bankrupt? “Two ways: Gradually, then suddenly.”

GUEST POST 💄

LinkedIn Just Voluntarily Tanked Their Algorithm (+ How To Win)

I’m old enough to remember when Sahil Bloom and his gang of Twitter threadboiis were printing cash. A time when culture and narrative all lived on Twitter, and when LinkedIn was primarily known to be where the business nerds hung out. Well, the site that began as an online resume is still the dorky stepbrother, but threaboii’ing is dead, the culture on Twitter X is rotten to its core, and there is only one place where money is made online today: LinkedIn.

While your LinkedIn follower count is never going to get you invited to a courtside NBA date with Kendall Jenner, it can work wonders for everything from bolstering your employer brand to raising money quickly and easily to building an incredible amount of pipeline for you and yours. When the little blue bird gave its last pre-X chirp, the business building baton was officially passed from one platform to another.

How does LinkedIn actually work in 2026, though? Is it threads (no)? Is it rage bait (no)? Is it posting 8,475 times per hour (maybe)? I, for one, have no bloody idea how it works. As a result, I’ve recruited my buddy Perrin Carrell, who runs Playbookz, to educate us. Perrin, the walking, talking algorithm nerd that he is, is the perfect man for this. He has helped execs from Framer, Trainual, Manila, and more build a 10x personal brand. Over to you, Perrin.

The state of things today

Hey team, Perrin here. As you might have seen from the title, LinkedIn blew up its algorithm. If you feel like you woke up one day, and suddenly no one cared what you had to say—unless you decide to become an asshole—it’s probably not you. Everyone’s noticed it. Q3 2025 analysis of 300k+ posts shows organic reach is down 65% from peak, median impressions down 18% year over year, and average creators growing 20% slower. It’s now 10x harder to get reach, harder to grow followers, and harder to make money on LinkedIn.

Source: Swipe Insight (older data but directionally correct).

Is it the LiNkEdIn ApOcAlYpSe?? Not exactly. Yes, it’s a hell of a lot harder. But really, what’s happened is that strategies that used to be effective stopped working and have been replaced with new ones. Doesn’t mean it’s not painful. It is. But people are absolutely still figuring out ways to win (and the best emerging strategies are leading to massively outsized wins; more on that below).

2020: The golden era of LinkedIn $$$$ printing

When 2020 hit, LinkedIn turned into a strange little attention vacuum almost overnight. Conferences died, offices emptied; the whole debacle. And for a lot of people, the feed quietly became the closest thing to ‘the industry’ they had left. But the platform wasn’t mature yet. So, two things were happening: everyone just kind of showed up on LinkedIn, and at the time, only about 1% of LinkedIn members posted weekly.

That accounted for about 3 million of 700 million people, and they shared an estimated 9 billion weekly impressions. It really was a vacuum. LinkedIn responded by whacking open the distribution spigot allllllllll the way. It was stupid. And it was amazing. Literally any doofus who could rattle off a quote about ‘leadership’ or ‘culture’ could build a following. And if you had an image to go along with your text???!

From 2020 to 2023, a small handful of good creators saw the opportunity and stepped into the vacuum. Some became wildly successful solopreneurs. Justin Welsh, an ex‑SaaS exec, started posting daily on LinkedIn around 2018–2019 (saw the vacuum early) and turned a single profile into a media business. He grew to 250k+ followers by 2022 and 630k+ by 2024, building a $10M+ one‑person company at ~90% margins off products like his LinkedIn Operating System and newsletter.

Others built small companies really fast. Andy Mewborn co‑founded Taplio in 2021 and used daily ‘build in public’ LinkedIn content as his primary GTM. In about a year, that attention took Taplio from $0 to roughly $1M in ARR, leading to an acquisition by Lempire and effectively turning posts into a growth engine. Andrew would go on to launch VC-backed Distribute—which now has 15,000 users across Deel, Gong, ClickUp, and more—largely off the back of his audience.

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And a few built 8-figure+ companies. Adam Robinson treated LinkedIn as the loudhailer for Retention.com, posting aggressively about email, churn, and spicy growth tactics from 2019 onward. That founder‑led presence helped bootstrap the company to roughly $20M–22M in ARR with a six‑person team, showing a CEO could use the same attention arbitrage to scale a capital‑efficient business.

Of course, that kind of vacuum never lasts. When you’ve got 1% of the platform hoovering up billions of impressions a week and turning them into seven‑ and eight‑figure businesses, the house eventually notices. And over the last 18 months, LinkedIn has started quietly closing the spigot it opened in 2020.

The day the algorithm grew up

It's tough to tell exactly what happens under the hood of a platform, but virtually everyone who measures the LinkedIn algo is seeing more or less the same thing. A Q3 2025 analysis of 318,842 posts found organic reach down 65% from its peak, median impressions down 18% year over year, and average creators growing 20% slower than the previous quarter (Chris Donnelly / Will McTighe). Another Q3 breakdown of 300k+ posts pegs organic reach at roughly 64% below 2022–2023 levels, even as engagement rates are up about 12% because far fewer posts get shown at all.

Operator reports point in the same direction. Multiple creators say they have lost roughly half their reach in 2025, with typical post views sliding from 10–20k down to 3–5k. Company pages are getting hit hardest: several 2025 breakdowns show the average company post now reaching only about 1.6% of followers, with brand content making up just 1–2% of the feed, down from around 7% a few years ago.

_{*Note: Below are a bunch of snapshots into the state of LinkedIn as of late 2025.}

Source: Social Insider.

Source: Social Insider.

Source: Social Insider.

Source: Social Insider.

At the same time, 2025 LinkedIn benchmark studies show engagement per impression creeping up while total impressions shrink, meaning fewer posts get real distribution, but the ones that do tend to perform strongly. Why? Basically, because LinkedIn got a new brain called 360Brew. And it’s pretty much like moving from a jumble of outdated algos to a single, AI-driven nervous system. LinkedIn used to run on a messy stack of different models: one to rank your feed, others to suggest jobs, others to recommend people you may know, and so on. Each had its own rules, features, and data pipelines. Over 2024–2025, LinkedIn started replacing that whole zoo with one giant brain called 360Brew.

Unsure of the context.

360Brew is a 150-billion-parameter, decoder-only foundation model, the same class of architecture as models like GPT, trained mostly on LinkedIn’s own first-party data: profiles, posts, job listings, applications, messages, and interaction history outside the EU.

Instead of feeding it a bunch of hand-built data fields, LinkedIn gives it text: task instructions like ‘rank feed posts for this member,’ snippets of your profile, your past behavior, and candidate items. The model predicts what you’re most likely to click, read, or act on next. That single model now handles 30+ predictive tasks across feed, search, jobs, people, and recommendations, often matching or beating the legacy systems it replaces. Think of it as LinkedIn strapping a PhD-level AI to the feed and letting it decide who sees what, and why. In other words, LinkedIn reads you now.

360Brew actually parses your headline, About section, posts, comments, and job history to decide what you’re about and who should see you, not just how many likes you got. Profile-content alignment matters more than ever. If your profile screams ‘B2B SaaS CEO’ but your posts are generic hustle quotes, the model gets a fuzzy signal, and you lose distribution. Relevance beats relationships. The feed has shifted from ‘who you know’ to ‘what’s relevant.’ Your content now competes across the whole network for people interested in that topic, not just your direct connections.

Cold starts are less hopeless, too. Because the model learns from text and patterns, it can match good niche content to the right people faster, even if your audience is small, as long as your topic and language are clear. That’s a huge change from the old LinkedIn, where distribution mostly depended on existing network strength and engagement history.

Patiently waiting for virtality to hit.

And finally, shallow hacks stand out as noise. Engagement pods, random virality plays, and off-topic posting create inconsistent signals that this unified model can spot and quietly down-rank. That’s why the old ‘just post more and hope the algorithm likes you’ playbook stopped working. There isn’t one dumb algorithm anymore; there’s a single, very opinionated model reading every move you make. Kinda sucks. But also kinda doesn’t.

The old stuff broke, but here's how to fix it

So, the old strategy of just having a pulse and hitting the publish button no longer works. But that absolutely does not mean nothing is working. I’m living proof. Not-so-humble brag: over the last 12 months, I’ve generated ~3.5M views, 6,000+ leads, and ~$1M in new revenue for a relatively tight book of clients.

I helped one of my clients land a contract with Experian, a 7 billion dollar company. I helped another sign Squarespace, a 1 billion dollar company. I also generated calls with Adobe, Mercedes-Benz, and more. LinkedIn is different. But holy shit, you bet your ass it still works. We do it every day. If you want to make a pivot, here’s what works for us.

1/ Write for customer problems

360Brew is constantly trying to parse what you're about. Everything you do needs to speak to the exact customer you want to work with: your banner, your headline, your featured content, your posts, and your comments on other posts. Specificity about a singular problem = semantic relevance. This is NOT fluffy advice. It’s literally how the machine works now.

Source.

2/ Create a ‘stack’ of the subchannels inside LinkedIn

The old way was to get organic reach and win. The new way is to combine organic reach, broad paid reach, narrow ABM-style paid reach, outbound DMs, and other ads. To be clear, this is the single most important thing. Each of those used to be kind of its own channel. Now, you need the stack. They feed each other: content creates a warm audience and engagement testing, which leads to cheaper paid reach, which makes outbound DMs warmer and more effective. We still do have clients seeing success with ‘just’ content. But the ones who are really crushing it are leaning into the full stack of marketing subchannels on the platform.

3/ Give away value

I’m sure you’ve seen lead magnets on LinkedIn. They’re the posts that have something cool, and do the whole ‘Comment CRM GUIDE! and I’ll DM you.’ If you haven’t, here’s an example of one we did for a client.

Source.

You’ve seen them a lot because they work like crazy right now. I don’t think they’ll work forever, but they check so many of the boxes of what matters to LinkedIn: they’re built to solve a specific problem for a specific person, they’re value-driven and build tons of context with semantically relevant engagement, and they play super well with the ‘legacy’ parts of the algorithm (e.g., ‘engagement = good.’)

But here’s the important part: you should give it away in all parts of your ‘stack.' Content, outbound, ads, all of it. When our clients are landing really big accounts, this is almost always how they’re doing it.

Bonus angle: Stand out by being different

If you want to build a legitimate personal brand on LinkedIn, you absolutely need to stand out. For all intents and purposes, you can stand out in two ways: (1) add tons of value, or (2) have a personality people really like. A really good example is James Hawkins, the CEO of PostHog. James is blowing up and going viral regularly with a strategy that is almost entirely shitposting. Look at the examples below.

Source.

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It’s funny. It’s tongue-in-cheek. And it invites people into a conversation that mocks the platform they’re on. And the spoiler alert is that hardly anyone likes being on LinkedIn, so it’s something people are really eager to do. The major caveat is that these posts are not designed to generate business; they're designed to create goodwill. PostHog is highly popular for its brand, design, and tone of voice. James's shitposting works as it fully aligns with the company.

Told you it was weird.

Another important caveat is that, to build this kind of brand, you have to be funny. If you try to do this thing without actually being funny, you usually just end up looking like an asshole.

Playbook / how you can apply this

Hopefully, you’ve seen some opportunities in the strategies listed above that you can apply to your own company. Here are five key takeaways.

• Define your one true audience: Create a content strategy that continuously targets a hyper-specific avatar—and then actually try to help them solve problems.

• Stack all three subchannels: Combine organic content with thought leader ads, ABM campaigns, and targeted outbound DMs for compounding effects.

• Layer on top-performing design: Use carousels and detailed infographics consistently. They outperform text posts and keep people engaged longer on platform.

• Productize what you know: Slice off chunks of your expertise and offer them as ‘comment to get this’-style lead magnets.

• Consistency is the moat: Post 3-5x weekly for 90-120 days minimum. Most quit early. Persistence creates the actual separation from competitors.

Future

It's going to get harder. Probably a lot harder. 360Brew is barely a year into its rollout, and it's already nuked most people's reach. As the model gets smarter and LinkedIn keeps tightening the screws to push more people toward paid products, the gap between people running a real strategy and people just ‘posting’ will widen into a canyon. The days of winging it and seeing what sticks are cooked.

But that's kind of the whole point. Most people on LinkedIn are still running 2021 playbooks. Generic thought leadership, sporadic posting, zero paid amplification, zero outbound. The bar for good is way higher than it used to be. But the bar for average hasn't moved at all, which means if you're willing to get specific, stack your channels, and actually commit? You're going to stand out more, not less.

My bet is that LinkedIn starts to look a lot like Google did in the mid-2010s. The organic-only window is closing. The pay-to-play layer is getting thicker every quarter. But the people who figured out how to blend both early; they owned their categories for years. We're in that exact window right now. Build the stack today, or write a LinkedIn post in two years about how LinkedIn doesn't work anymore. Your call.

Extra reading / learning

• My $1M content marketing framework - August, 2023

• How to build an army who will happily promote your content for you - April, 2024

And that’s it! You can follow Perrin on LinkedIn or check out Playbookz on their website to keep up with what they’re building!

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

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TOOLS WE RECOMMEND 🛠️

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