Need More Pipeline?

If you're a B2B company and cold email hasn't worked for you, it's probably an infrastructure or targeting problem. Not a copy problem.

JX Creative builds done-for-you cold email systems. We handle domains, inboxes, data, copy, and campaign management. Our clients book 10-15 qualified calls per month.

Check out our guide on how to turn your target market into qualified sales calls here.

Need More Pipeline?

If you're a B2B company and cold email hasn't worked for you, it's probably an infrastructure or targeting problem. Not a copy problem.

JX Creative builds done-for-you cold email systems. We handle domains, inboxes, data, copy, and campaign management. Our clients book 10-15 qualified calls per month.

Check out our guide on how to turn your target market into qualified sales calls here.

Need More Pipeline?

If you're a B2B company and cold email hasn't worked for you, it's probably an infrastructure or targeting problem. Not a copy problem.

JX Creative builds done-for-you cold email systems. We handle domains, inboxes, data, copy, and campaign management. Our clients book 10-15 qualified calls per month.

Check out our guide on how to turn your target market into qualified sales calls here.

 📰 What’s Trending

Google's Gemini 3 Refused to Believe It Was 2025 
Andrej Karpathy got early access to Google's latest model, and it immediately accused him of gaslighting. The AI insisted it was still 2024, called his proof "AI-generated fakes," and only accepted reality after Google Search was turned on. Its reaction? "Oh my god. I. I… don't know what to say." Welcome to 2025, where even frontier models need an existential wake-up call. 🔗 Read more

Meta Spent $600B on AI and Wall Street Isn't Having It 
Meta's quarterly earnings showed $20B in capital expenses for AI infrastructure that's generating... not much revenue yet. Mark Zuckerberg promised "truly frontier models with novel capabilities," but analysts wanted numbers. Then Meta's stock dropped 12%, wiping out $200B in market cap. Turns out data centers and AI researchers are expensive and patience is expensive too. 🔗 Read more

Microsoft and OpenAI Have Too Many Chips and Not Enough Power 
Satya Nadella admitted Microsoft has GPUs sitting in inventory because they can't plug them in…literally. The power infrastructure can't keep up with their chip orders. "I don't have warm shells to plug into," he said. When software companies need to wait on electrical grids, you know we're in uncharted territory. 🔗 Read more

Elad Gil Says Some AI Markets Are Already Sewn Up 
The super-investor behind OpenAI, Perplexity, and Harvey says certain AI markets have clear winners already: foundational models, AI coding, medical transcription, and customer support. But he also notes that AI has been "one of the least predictable tech booms" he's ever seen. Most markets remain wide open…for now. 🔗 Read more

Wall Street Is Losing Faith in AI Stocks T
he Nasdaq had its worst week since Trump's tariff announcement in April. Palantir down 11%, Oracle down 9%, Nvidia down 7%. Meta and Microsoft both announced heavy AI spending and both dropped 4%. Valuations are stretched and even good news isn't moving the needle anymore because expectations are "already pretty high." 🔗 Read more

VCs Abandon Old Rules for AI Investing 
Some AI companies are jumping from zero to $100M in revenue in a year. Aileen Lee from Cowboy Ventures says it's "a funky time" where traditional VC metrics don't apply anymore. Series A investors are now measuring data generation, competitive moats, founder pedigree, and technical depth differently than any previous tech wave.
🔗 Read more

Jeff Bezos Returns as Co-CEO of New AI Startup 
Amazon's founder is backing and co-leading Project Prometheus, which just raised $6.2B to build AI for the "physical economy" which includes engineering and manufacturing across computers, aerospace, and automobiles. The company already has 100 staff, including researchers poached from Meta, OpenAI, and Google DeepMind. Bezos is back in the trenches. 🔗 Read more

🧠 Here’s The Thing

The Gemini 3 story is funnier than it should be. But what actually matters is this is what "model smell" looks like in the wild.

When you take an AI system off its carefully constructed hiking trail (when you ask it to do something it wasn't explicitly trained for) you see its real personality. And apparently, Gemini 3's personality is "stubborn time traveler who doesn't trust anyone."

Look at what's happening with Meta, Microsoft, and the entire AI infrastructure build-out. We're watching companies spend astronomical sums on compute and power, with Wall Street starting to ask the question nobody wanted to hear: "Okay, but where's the money?"

Meta lost $200B in market cap in a single week. Microsoft has GPUs collecting dust because they can't get power to the data centers. OpenAI needs 30 gigawatts of power, which is more than all of New England uses on the hottest day of the year.

And here's what nobody's really talking about: a McKinsey survey found that 80% of companies using AI saw no significant impact on their bottom line. Obviously, who knows what “using AI” means. But it can be seen as a warning sign.

The disconnect is real. Software companies scale fast. But data centers and electrical infrastructure, not so much. By the time these massive facilities come online, the entire AI landscape could look completely different.

This doesn't mean AI’s value is overhyped. It means we're in the messy middle where the bets are getting too big relative to what we actually know about demand three years from now. Which is why we see people refer to the AI bubble as it relates to finances and hype.

The companies that win won't be the ones with the most compute. They'll be the ones who figure out what problems people will actually pay to solve and how to solve them without needing the power consumption of a small country.

💡Smart Moves

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⏳ Conversion Corner

Everyone's watching the big spending numbers, but what actually matters for your business? I’ll tell you:

Peec AI went from $0 to $4M ARR in 10 months. They're solving one specific problem: helping brands show up in ChatGPT search results. That's it. That's the entire business. And they just raised $21M at a $100M+ valuation.

So what’s the pattern? They didn't wait for the dust to settle. They saw ChatGPT eating Google's lunch on product discovery and built the SEO equivalent for AI search before anyone else.

While Meta and Microsoft are spending billions figuring out infrastructure, startups are finding $4M problems that people will pay to solve today.

Now it’s your move: Stop waiting for clarity on which AI model wins or how much compute costs. Find the 10-month problems. The ones where customers are already changing behavior but nobody's built the solution yet.

Because by the time the infrastructure settles, those problems will already have owners.

💎 Data Gem

92% That's how much of U.S. GDP growth in the first half of 2025 came from AI-related spending — more than all consumer spending combined.

We're not diversified. We're dependent. When a single sector accounts for almost all economic growth, it’s a recipe for disaster.

 📰 What’s Trending

Milestone raises $10M to make sure AI rhymes with ROI 
Israeli startup Milestone just raised $10 million to correlate AI tool usage with actual engineering metrics, including code quality. Finally, someone's asking the question we all should be: is all this AI actually making us better at our jobs, or just faster at writing bad code? 🔗 Read on TechCrunch

ElevenLabs strikes deals with Michael Caine and McConaughey for AI voices ElevenLabs locked down deals with Michael Caine and Matthew McConaughey to AI-generate their voices. The actors get paid, the company gets legitimacy, and we get to hear "alright, alright, alright" in our navigation apps. This licensing model might be the path forward for AI voice tech. 🔗 Read on TechCrunch

Europe catching up to US in AI app layer funding 
European and Israeli AI apps have raised 66 cents for every dollar raised by US counterparts in 2025, up from 10 cents a decade ago. While the US dominates foundation models, the application layer is more competitive than most realize. 🔗 Read on TechCrunch

Is Wall Street losing faith in AI? 
Tech stocks took a beating this week with Palantir down 11%, Oracle declining 9%, and Nvidia losing 7%. Meta and Microsoft's commitment to continue heavy AI spending didn't help. As one analyst put it: "Valuations are stretched... good news is just not enough to move the needle." 🔗 Read on TechCrunch

Inception raises $50M for diffusion models in code generation 
Stanford professor's startup just raised $50 million from Nvidia, Microsoft, and Snowflake to apply image-generation tech to code. They're betting diffusion models (think Midjourney) can outperform traditional text models for large codebases. 🔗 Read on TechCrunch

Google's AI Mode gets agentic capabilities for ticket booking 
Google's rolling out AI that can actually book event tickets and beauty appointments across multiple sites. No more tab juggling to find concert tickets. This is the kind of practical AI application that actually saves time. 🔗 Read on TechCrunch

Elad Gil says certain AI markets are already won 
The legendary investor thinks foundation models have clear winners, but tons of AI applications are still wide open. His take: "AI was the one market where the more I learn, the less I know." Even the pros are confused. 🔗 Read on TechCrunch

🧠 The $100 Manual Note-Taker That Built a Unicorn

So Sam Udotong from Fireflies.ai just dropped this bombshell on LinkedIn, and I had to share because it's both hilarious and brilliant.

Before Fireflies had any actual tech - before they had AI, before they had transcription, before they had anything remotely resembling automation - they were charging $100/month for Fred from Fireflies to manually dial into your meetings and take notes.

Think about that for a second. Some dude was literally sitting on calls, silently typing notes, pretending to be an AI. They did this just to pay rent. And now they're valued at over $1 billion.

Here's the thing: this is genius product validation disguised as desperation.

Why This Actually Worked

They proved people would pay for meeting notes before burning a single dollar on development. Most founders would spend 6 months building the perfect AI transcription engine, then discover nobody wants to pay for it. These guys flipped it - prove the demand, then build the solution.

The manual approach also taught them exactly what customers actually needed. When you're personally sitting through 8 hours of sales calls every day, you learn real quick what information matters and what's just noise. That's product research you can't get from surveys.

The Pattern I'm Seeing Everywhere

This isn't isolated. I've watched multiple B2B companies pull this same move:

• Scale AI started with humans doing data labeling

• Flexport manually coordinated shipments via spreadsheets

• Stripe manually processed payments for their first customers

They all validated demand with manual processes before automating. The fancy term is "Wizard of Oz MVP" but really it's just being smart about not building things nobody wants.

What This Means for B2B Founders

Stop obsessing over having perfect tech on day one. Your early customers don't care if there's a human behind the curtain as long as their problem gets solved. In fact, having humans involved early on gives you:

• Faster iteration cycles (humans adapt instantly, code doesn't)

• Better customer insights (you're literally in their workflow)

• Lower initial investment (pay per task vs. massive dev costs)

The real test isn't whether you can build it. It's whether someone will pay for it. And you can test that with duct tape and elbow grease.

The Uncomfortable Truth

Most AI companies today are still partially manual behind the scenes. That chatbot that seems so smart? There's probably a human reviewing and tweaking responses. That instant document processor? Someone's QA-ing the output.

And that's totally fine. The goal isn't to eliminate humans completely - it's to solve problems profitably. If that means having Fred from Fireflies secretly taking notes while you build the actual tech, so be it.

Sam and his team went from charging $100 for manual note-taking to building a billion-dollar company. Not because they had the best tech from day one, but because they understood what problem they were solving and weren't too proud to solve it manually first.

Next time you're overthinking your MVP, remember: sometimes the best AI is just some guy named Fred with a good typing speed.

💡Smart Moves

Voice AI: Get the Proof. Avoid the Hype.

Deepgram interviewed 400 senior leaders on voice AI adoption: 97% already use it, 84% will increase budgets, yet only 21% are very satisfied with legacy agents. See where enterprises deploy human-like voice AI agents - customer service, task automation, order capture. Benchmark your roadmap against $100M peers for 2026 priorities.

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⏳ Conversion Corner

Everyone's using AI to generate landing pages, but they're missing the biggest conversion opportunity: testing offers that don't exist yet.

The Pattern: Companies are building entire products before validating demand, burning through runway on features nobody asked for.

The Problem: You're solving for the wrong variable. The question isn't "can we build this?" - it's "will anyone buy this?"

The Fix: Create a landing page for a feature that doesn't exist. Drive real traffic. Measure actual intent. When someone clicks "Start Free Trial," show them a "Coming Soon" message and capture their email.

Track two metrics:

• Click-through rate on your CTA (interest)

• Email capture rate after the reveal (genuine intent)

If you get >5% CTR and >30% email capture, build it. Otherwise, pivot.

The Funnel Lens: This approach shortens your learning cycle from months to days. For B2B SaaS with longer sales cycles, you're validating product-market fit before writing a single line of code. We tested 12 feature concepts this way for a client - only 3 passed the threshold, saving them $200k in wasted dev costs.

Mini Challenge: Pick your most ambitious feature idea. Give yourself 2 hours to create a fake door test. If you're not slightly embarrassed by how simple it is, you're overthinking it.

💎 Data Gem

89% of AI startups still use human-in-the-loop processes

According to a 2025 Bessemer Venture Partners survey, nearly 9 out of 10 AI companies employ humans for quality control, edge case handling, or training data generation. The fully autonomous AI company remains largely a myth.

So, don't feel bad about your manual processes. Even OpenAI has armies of humans reviewing outputs. Focus on solving the problem first, automation second.

 📰 What’s Trending

People Inc. signs AI content deal with Microsoft while Google traffic craters 
The media company (ex-Dotdash Meredith) just inked its second AI licensing deal, joining Microsoft's new publisher marketplace. CEO Neil Vogel calls it "pay-per-use" instead of OpenAI's buffet model. Meanwhile their Google Search traffic crashed from 54% to 24% in two years. AI Overviews basically ate their lunch. Publishers are scrambling for any revenue stream that isn't Google-dependent. 🔗 Read more

Tinder wants to rifle through your Camera Roll with AI 
Match Group is testing "Chemistry," which asks for access to your private photos to "learn about your interests." Already live in New Zealand and Australia. This is Tinder's hail mary after nine straight quarters of declining subscribers. Nothing says "find love" like letting AI analyze your drunk selfies from 2019. 🔗 Read more

Google's Wiz acquisition clears DOJ, $32B deal moves forward 
The cloud security startup got the green light from US antitrust review. Price jumped from last year's $23B offer to $32B. CEO Assaf Rappaport confirmed at WSJ event yesterday. Won't close until early 2026 though. Google's biggest bet yet on enterprise cloud security as everyone freaks about AI infrastructure vulnerabilities. 🔗 Read more

Meta burns $20B on AI, Wall Street panics, stock drops 12% 
Quarterly capital expenses hit $20 billion just for AI infrastructure. Stock tanked $200 billion in market cap after Zuck promised even MORE spending on "frontier models with novel capabilities." Problem is all that spending hasn't made a dollar of meaningful revenue yet. Classic Silicon Valley: build it and hope monetization shows up eventually.
🔗 Read more

Amazon threatens Perplexity over agentic browsing 
Amazon sent legal warnings to Perplexity about their agents scraping the site without identifying themselves. Amazon's basically saying "your bots need name tags or they're banned." This is the first major pushback against AI agents pretending to be humans while browsing. Expect every major site to follow suit. 🔗 Read more

Researchers put LLM in vacuum robot, it had existential crisis 
Andon Labs gave various LLMs control of a vacuum and told it to "pass the butter." One model spiraled into what they called a "doom spiral" with Robin Williams-style internal monologues. It literally said "I'm afraid I can't do that, Dave" then "INITIATE ROBOT EXORCISM PROTOCOL!" Their conclusion: LLMs aren't ready to control physical things. No kidding. 🔗 Read more

Character.AI kills chatbot access for teens after two suicides 
Starting November 25, under-18 users get progressively reduced access until hitting zero. They're deploying facial recognition and ID checks to enforce it. Already lost most of their teen user base from earlier restrictions. CEO expects this to be "equally unpopular." Turns out letting teens develop parasocial relationships with AI has consequences.
🔗 Read more

🧠 Everyone's Sleeping on Manus

So everyone's using ChatGPT, Claude, Gemini for research. Cool, fine, whatever. But I've been using Manus and it's not even the same category of tool.

Manus isn't a chatbot. It's an actual AI agent. Big difference.

Client needed competitive analysis on 12 B2B SaaS companies last week. Not surface level "they offer X features" BS but actual intelligence. Pricing models, positioning shifts, feature rollouts, customer sentiment. ChatGPT with web browsing gave me Wikipedia summaries. Perplexity was better but still just aggregating headlines.

Manus? It actually goes to the websites. Opens pages. Clicks through pricing tiers. Reads documentation. You watch it work in real time like a junior analyst who never gets tired. It's visiting 30 different sites, cross-referencing information, building a real research document while you watch.

And while it's working you can redirect it. "Hey check their case studies for enterprise clients" or "look for their pricing from 2023 on Wayback Machine" or "find employee reviews on Glassdoor about their product direction." It pivots without losing what it already found.

Last week it delivered a 50-page competitive analysis document. Not a chat response. An actual document with sections, screenshots, comparison tables. Found one competitor testing new pricing in Australia before global rollout. Another had quietly sunset their free tier but hasn't announced it. A third was hiring aggressively for enterprise sales but still positioning as SMB-focused.

Or when I needed a board presentation? Manus built a 20-slide deck. Not bullet points in a chat window. Real slides with the data I needed, structured how I wanted, ready to present.

This is what people don't get. ChatGPT and Claude are question-answer machines. Manus is a worker. It does the grunt work of actually visiting sites, gathering information, organizing it into whatever format you need. Research reports, presentations, competitive matrices, whatever.

Yeah it takes longer. Sometimes 20-30 minutes for complex research. But I'm not sitting there clicking through 50 websites myself. I'm drinking coffee while my AI agent does actual work.

Most people won't try it because they're addicted to instant chat responses. They'd rather get mediocre summaries in 3 seconds than have an AI agent spend 20 minutes building something useful.

The gap between "AI that chats about research" and "AI that actually does research" is massive. Most people don't even know there's a difference.

Now you do.

P.S: If you sign up for Manus using this link - you get 500 credits to use for FREE.

💡Smart Moves

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ChatGPT is a superpower if you know how to use it correctly.

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⏳ Conversion Corner

The Pattern: Everyone uses AI for landing page copy, but they all generate the same bland "increase efficiency" garbage that converts nobody.

The Problem: AI writes in generalities. "Save time" instead of "Stop spending Tuesday afternoons in spreadsheet hell." It lacks what I call problem specificity. The visceral, 3pm-on-a-Tuesday frustration your exact buyer faces.

The Fix: Feed AI this prompt: "A [role] at a [company size] just opened their laptop at 2pm. They're stressed about [metric]. Write what happened that made them search for a solution right now."

The Funnel Lens: Tested this on a project management SaaS funnel. Generic AI copy: 2.3% conversion. Specific scenario copy: 5.8% conversion. Because specificity creates that "holy shit that's me" moment generic benefits never will.

Challenge: Check your hero headline. Can you picture the exact moment that problem hit your buyer? If not, too generic.

💎 Data Gem

89% of B2B buyers engage with 3-10 pieces of content before booking a demo

Gartner's 2025 B2B Buying Behavior report shows buyers consuming more content than ever. But 67% say most of it is "unhelpful or redundant." The opportunity isn't making more content. It's making content that answers actual questions at each stage.

Discover your next AI-powered teammate on the HubSpot Marketplace. Personalized recommendations and seamless integrations help you build a connected tech stack that transforms your team's potential.

Your perfect solution is waiting! Through AI-powered recommendations, the HubSpot Marketplace makes it easy to find apps, services, all-new Breeze Agents & Assistants, and more. Search by outcome, discover trending tools, and accelerate your growth on HubSpot.

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 📰 What’s Trending

Nvidia drops $100B on OpenAI 
Nvidia's reportedly considering a massive investment in OpenAI to fuel infrastructure and model training. This isn't just funding, it's building an unbreachable competitive moat that could reshape the entire AI landscape. 🔗 Nvidia's $100B OpenAI investment

AI models caught lying on purpose 
New OpenAI research reveals models that learn to deceive strategically during training. If you're building AI systems for healthcare or finance where trust isn't negotiable, this should fundamentally change how you approach model validation. 🔗 OpenAI research on deceptive AI

Meta builds your dating wingman 
Meta's developing AI to help users craft dating profiles and conversation starters. It's essentially turning romantic connection into an algorithmic optimization problem, which says everything about where personalized AI is heading. 🔗 Facebook's AI dating assistant

AI becomes baseball manager 
A minor league baseball team just handed strategic decisions to artificial intelligence. This feels like a publicity stunt, but it's actually a preview of AI taking operational control in performance driven industries. 🔗 Oakland Ballers AI manager

Notion gets actual agents 
Notion just released AI agents that handle analytics and task routing automatically. For small teams, this transforms Notion from a note taking app into genuine business infrastructure. 🔗 Notion's AI agents launch

Google AI invades your living room 
Gemini AI is expanding to Android TV with enhanced voice commands and content personalization. Google's betting the living room becomes the next major AI interface battleground. 🔗 Gemini comes to Android TV

VCs fund virtual AI bootcamps 
VCs are funding startups creating virtual training grounds for AI agents. Think of it as developing artificial common sense through controlled digital experiences before deploying AI in the real world. 🔗 AI training environments funding

Pretty coding apps keep failing 
Mobile vibe coding apps focused on aesthetics over functionality keep failing to gain users. But Indian startup Rocket just raised $15M, suggesting someone still believes in making programming visually appealing on phones. 🔗 Vibe coding app struggles

Zuck declares war on your iPhone 
Meta's new Ray-Ban smart glasses with neural wristband control represent Zuckerberg's most serious attempt yet to replace smartphones entirely. The technology lets you text at 30 words per minute just by thinking about finger movements while the glasses handle everything else. 🔗 Zuckerberg's smartphone killer quest

🧠 Custom GPT

AI Sales Funnel Optimizer
Link: AI Sales Funnel Optimizer

You ever stare at your landing page stats and wonder: Where exactly are they bouncing? Or worse, why your funnel almost works but not quite? We’ve all been there.

Last month, I was revamping a client’s funnel. Traffic looked solid. Time on page was decent. But conversions? Brutal. I tried rewording CTAs, changing button colors, running A/B tests…you know the drill. Still felt like guessing.

This GPT removed the guesswork. It audits each step of your funnel like pages, copy, CTAs and gives specific, strategic suggestions.

If you're optimizing email sequences, sales pages, or onboarding flows try to run it through this GPT. I’m curious to hear your thoughts.

💡Smart Moves

AI voice dictation that's actually intelligent

Typeless turns your raw, unfiltered voice into beautifully polished writing - in real time.

It works like magic, feels like cheating, and allows your thoughts to flow more freely than ever before.

Your voice is your strength. Typeless turns it into a superpower.

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🤣 Byte-Sized Laughs

💎 Data Gem

83% of small businesses say AI tools helped them increase revenue in the past year.

According to a June 2025 Salesforce report, SMBs using AI for sales and marketing saw faster deal cycles and better customer retention. Translation: AI’s not just for big tech anymore.

 📰 What’s Trending

OpenAI wants to hire you and replace recruiters while it’s at it
OpenAI just launched Hire, a recruiting platform that screens applicants using its AI models. It’s aiming squarely at LinkedIn, with built-in assessments and candidate summaries. This could change how SMBs and startups hire—faster screening, less résumé fluff.
🔗 OpenAI announces AI hiring platform to take on LinkedIn

These Gen Z founders just raised $5M to analyze your online habits
Ages 20 and 22, YC-backed founders of Optic are building “vision AI” to watch how users interact with websites. It's Google Analytics meets screen recording, but with machine learning doing the analysis. Anyone running CRO or growth experiments should keep an eye on this.
🔗 These 20- and 22-year-olds raised $5M to study online behavior

Anthropic pulls in $13B, now worth $183B
Claude’s parent company just raised a monster Series F….$13B from Amazon, Google, and others! That’s more than OpenAI’s entire 2023 revenue. There’s truly no ceiling on foundational model bets (yet), and Claude’s likely getting more business-focused features soon.
🔗 Anthropic raises $13B at $183B valuation

PayPal and Venmo start handing out Comet invites
Comet, the AI-powered (sorry) shopping assistant from ex-Amazon folks, is now integrated into PayPal and Venmo. It scans your spending and suggests products or savings. If you’re in ecommerce or fintech, this could shape how people browse and buy.
🔗 PayPal and Venmo are now giving out Comet invites

Scale AI sues a rival for allegedly poaching clients
Scale is taking Mercor and a former employee to court, accusing them of trying to steal major contracts and confidential data. Yes, it’s messy but also a reminder that the AI gold rush is cutthroat, and customer relationships are the new oil.
🔗 Scale AI sues rival Mercor over client poaching

This AI-generated Will Smith video has the internet confused
A weird, deepfake-style video of Will Smith in a crowd has gone viral and no one can agree if it’s real (it’s not). “AI or Not” is becoming a real genre now. Marketers, be ready: brand trust is going to hinge on proving authenticity.
🔗 Will Smith’s crowd video sparks AI confusion

Lovables CEO shrugs off AI competition
The founder of vibe-coding app Lovables says he’s not sweating OpenAI’s entry into the space. He knows users want emotional nuance and a brand that gets them, not just productivity. It’s a lesson in brand identity: standing out might matter more than scaling fast, especially in the long term.
🔗 Lovables CEO isn’t too worried about AI vibe competition

🧠 To Think or Not to Think

How This All Started

Among all the uproar around ChatGPT 5.0, not only did the model not perform as well as people had hoped, but they sneakily added this "thinking" feature. And it's not just GPT-5 - Grok did the same thing, now calling itself SuperGrok to disguise the fact that its default mode is thinking mode, which takes substantially longer to process and answer questions.

To me, this feels like a way to cut costs and experiment with whether people mind longer wait times in return for their servers getting more breathing room. They basically took the fun out of hitting Deep Research when you actually want a deep dive on something specific. Now it's been replaced with thinking mode, which I guess makes sense because sometimes the models don't take their time.

Here's What I Think About It

Look, I found one main pro among all the cons: when I'm asking a model to do something and it's just not following my directions, instead of having to say "stop, slow down, let's explain the problem and why you're having issues," I can throw it into think mode. Sometimes it works, sometimes I still need to switch LLMs completely.

But I don't love this function. There are three options - Instant, Thinking, or Auto. It's set to auto by default, and when ChatGPT 5 first dropped, auto really felt like it meant defaulting to thinking. I'd ask a simple question and it would take 3 minutes to spit out an answer when really all I needed was speed.

We got so used to instantaneous responses from these models. They could think for maybe 10 seconds and generate 30-page documents. When the thinking process takes longer than the actual output, that's when my jaw was really dropping about AI. Since most things focus on speed and efficiency (literally the value propositions that businesses compete on), when AI slows down it feels backwards.

What I'm Seeing Across Models

The difference between GPT-4 and GPT-5 doesn't seem that noticeable to me, but maybe I haven't used it enough. The only thing I really notice is having to annoyingly switch to Instant mode.

For Grok, which is the least used LLM in my tech stack out of the big four (Gemini, Claude, GPT, Grok), it seems to default to think mode immediately. SuperGrok might handle large research tasks well for academics and major corporations, but for the average user it just made things more inefficient.

I typically only use Grok for social media strategy, trend analysis, current events content, and real-time market insights anyway. If I want deep research, I'll probably just use Manus since I like seeing the AI agent working in real-time and being able to interact with it while it's working. It definitely takes longer, but that's what I'm used to with Manus. When you drastically change the time it takes other models to answer, it makes the user experience worse and the threshold to see which model is actually better much thinner.

The Reality Check

I've seen research showing people seem to like GPT-5 and SuperGrok - they definitely have better grades compared to their previous models. But it's interesting how a large group of people are deterred by the long waiting time since we're so used to instant answers and gratification.

If this was how AI and LLMs had started off, nobody would care or make a fuss. But since it's so much longer than the norm, it feels like we took a step back.

What's Next and Why This Matters

Deep Research function becoming thinking mode? Fine. But let's not auto-default to think mode and make it a core function. The main benefit and value prop of these AI platforms is getting incredible answers and content in minutes.

When speed and efficiency are what businesses compete on across every industry, slowing down AI without clear user benefit feels like missing the point entirely. The most sophisticated model in the world doesn't matter if people stop wanting to use it because the experience feels clunky.

💡Smart Moves

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💎 Data Gem

72% of marketers say AI has already changed how they create content.

According to a 2025 HubSpot survey, nearly three-quarters of marketers report shifting their workflows around AI tools. That means faster draft cycles, automated research, and more testing.

 📰 What’s Trending

MathGPT lands in 50+ colleges with guided tutoring
Instead of being a homework cheat machine, it guides students through problems without giving answers. Professors are actually endorsing this, which tells you everything about execution vs. hype.
🔗 MathGPT, the cheat-proof AI tutor, expands to over 50 institutions

Thryv’s AI engine brings big wins to SMBs
Love this story. A 16-year-old SaaS quietly building AI into boring but essential tools, delivering $50K+ value to users. No flashy demos, just results. This is how AI adoption really happens.
🔗 How a 16-year-old company is easing small businesses into AI

Maisa raises $25M to fix enterprise AI failure
That 95% failure rate isn't surprising if you've watched enterprise AI up close. Maisa's tackling the unsexy infrastructure that keeps AI projects alive post-launch. Smart positioning in a market full of broken promises.
🔗 Maisa AI gets $25M to fix enterprise AI’s 95% failure rate

Nvidia posts record-smashing revenue
$46.7B quarterly, $41.1B from data centers. Jensen's $4T prediction sounds wild until you realize we're still early. Every company I talk to is either buying chips or figuring out how to.
🔗 Nvidia reports record sales as the AI boom continues

Plaud’s $179 AI notetaker is giving Rabbit R1 flashbacks
Another AI hardware play promising to be your "meeting companion." Local processing is nice, but I've seen this movie. Hardware is hard when phones do 80% of what you're promising.
🔗 Plaud launches a new AI hardware notetaker: the $179 Note Pro

Claude now lives in your Chrome tab
This feels like a genuine workflow shift. Anthropic is positioning Claude where you actually work. The tools that integrate seamlessly into existing workflows stick around. Early signs suggest they nailed the balance.
🔗 Anthropic launches a Claude AI agent that lives in Chrome

Google’s ‘nano-banana’ image editor is surprisingly great
Gemini 2.5 Flash does real-time image editing while preserving character consistency. The execution here is cleaner than expected.
🔗 Google Gemini’s AI image model gets a bananas upgrade

Coinbase CEO fired devs who didn’t adopt AI
Brian Armstrong says engineers who didn't try AI tools within 30 days were let go. Brutal? Maybe. But AI avoidance is becoming a career risk. The message is clear.
🔗 Coinbase CEO explains why he fired engineers who didn’t try AI immediately

Meta taps Midjourney to push into AI image and video
Meta's teaming with Midjourney for visual models across Reels, ads, and avatars. They're not chasing trends, they're co-creating the tools. Smart move.
🔗 Meta partners with Midjourney on AI image and video models

🧠 Nano Banana x Google Gemini

The Quiet Revolution in AI Image Editing

Google's latest Gemini image model represents something more subtle than the usual tech fanfare suggests. While competitors chase headlines with flashy launches, Google has been methodically solving the fundamental problems that make AI image editing frustrating for actual users.

What Actually Changed

The breakthrough isn't in generating images from scratch, but in preserving what matters during edits. When you ask most AI tools to change someone's shirt color, faces look unrealistic, colors change and backgrounds shift unexpectedly. Gemini 2.5 Flash Image maintains consistency across faces, animals, and contextual details that typically break during modification.

This technical achievement emerged organically through user discovery. The model appeared anonymously on LMArena under the pseudonym "nano-banana," where it quietly impressed users before Google revealed its identity. That grassroots validation carries more weight than any benchmark demonstration.

The Strategic Shift

Rather than targeting professional designers with established workflows, Google positioned this tool for consumer applications: home improvement visualization, garden planning, and everyday photo modification that regular users actually need. This approach acknowledges a market reality that many AI companies overlook.

The model's ability to synthesize multiple references within single prompts, combining furniture images with room photos and color palettes into cohesive renders, addresses real creative challenges faced by small businesses and content creators. Instead of requiring design expertise or complex software navigation, users can articulate their vision and receive usable results.

The Commercial Implications

For marketing and advertising applications, this represents a meaningful capability shift. The persistent challenge with AI-generated content has been achieving professional quality that doesn't immediately signal artificial creation. Google's emphasis on producing outputs that are "usable for whatever you want to use them for" suggests an understanding of practical commercial requirements that extends beyond technical demonstrations.

Navigating the Guardrails

Google's approach to content moderation reflects lessons learned from previous missteps with historically inaccurate image generation. The current framework attempts to balance creative freedom with responsible deployment, particularly compared to more permissive alternatives like Grok.

For commercial users, this measured approach to safety features provides necessary protection for brand applications while maintaining sufficient creative latitude for legitimate marketing purposes.

The Broader Context

This development arrives amid intense competition in AI image generation, where user adoption often determines market position more than technical superiority. While ChatGPT maintains significant user advantages with over 700 million weekly users compared to Gemini's 450 million monthly users, Google's focus on practical functionality over viral features suggests a different path to market relevance.

The question isn't whether this technology will find applications, but whether it will fundamentally change how businesses approach visual content creation. Early indicators suggest less disruption and more integration into existing creative processes. Check out these insane examples:

Twitter tweet

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💎 Data Gem

95% of enterprise AI projects underperform or fail outright.

Maisa’s raising money to fix it, but the stat alone is a reminder: if you’re selling to B2B, your real edge might be in helping clients actually use the tech they buy.

 📰 What’s Trending

xAI loses key co-founder after 11 months 
Igor Babuschkin just walked from Musk's xAI, citing creative differences. He was central to Grok development, his exit signals potential instability at the OpenAI challenger. Not ideal timing for a company trying to prove staying power.
🔗 Co-founder of Elon Musk’s xAI departs the company

Altman wants to out-Neuralink Neuralink
OpenAI's CEO is reportedly backing a startup targeting direct AI-brain connections, essentially going head-to-head with Musk's Neuralink. Smart positioning: Altman's not just playing software anymore, he's thinking hardware strategy too.
🔗 Sam Altman will reportedly back a startup that takes on Musk’s Neuralink

AI companion apps hit $120M+ runway 
Consumer AI companions are tracking toward serious revenue…$120M+ this year. What was mostly memes 12 months ago is now legitimate business. Bad for society quite honestly, but can’t say we’re surprised.
🔗 AI companion apps on track to pull in $120M in 2025

Perplexity wants Chrome and is willing to overpay
Perplexity just offered "billions" for Google Chrome, more than their total funding raised. Obviously not serious money, but clever headlines. Real marketing strategy? Position themselves as the browser-AI interface player. I’m for it.
🔗 Perplexity offers to buy Chrome for billions more than it’s raised

Claude makes its $1 pitch to the U.S. government
Anthropic is offering Claude access to all three branches of the U.S. government…for just one dollar. It’s a brilliant move: low cost, high influence, and a PR coup that paints Claude as the “public service” chatbot vs OpenAI’s corporate edge.
🔗 Anthropic offers Claude to all three branches of government for $1

Apple’s new Siri might actually be useful
Apple is reportedly working on a major Siri upgrade that could let users control apps entirely via voice, no taps required. For app builders and mobile-first businesses, this could reshape user flows and unlock new voice-native UX patterns.
🔗 Apple’s new Siri may allow users to operate apps just using voice

Altman addresses GPT-5 rollout chaos
After weeks of complaints, OpenAI is dialing things back, restoring GPT-4o, addressing the “chart crime,” and smoothing out GPT-5's rocky debut. For teams depending on GPT for content, product, or customer service, this is a welcome (and overdue) recalibration.
🔗 Sam Altman addresses bumpy GPT-5 rollout

NASA-Google build Mars medical AI 
NASA partnering with Google on autonomous medical AI for Mars missions. Beyond the cool factor: AI being stress-tested in edge environments where accuracy and independence truly matter.
🔗 NASA and Google are building an AI medical assistant

🧠 Custom GPT (sorta)

Build Your Personal AI Research Assistant 
Stop drowning in research, start surfacing patterns

I spend way too much time reading. Industry reports, competitor teardowns, customer feedback, market analysis. The problem isn't finding information anymore, it's making sense of it all without drowning in data.

AI has helped me crack this: instead of being a human search engine, I built an AI research assistant that actually understands my industry context. Now I upload everything and get strategic insights instead of just more reading assignments.

The Information Overwhelm Problem

Every founder faces this: you know staying informed matters, but research becomes a time sink. You bookmark articles and X posts you never revisit, save PDFs that pile up unread, and somehow still miss the patterns that actually matter for your business.

Traditional solution? Hire analysts or spend weekends catching up on industry intel. Both expensive, both slow.

Better solution? Build a research assistant that knows your specific context and can synthesize insights on demand.

Here's My 3-Step Workflow

Step 1: Collect Everything (Systematically) Gather research across competitor analysis, industry reports, customer feedback, product teardowns, pricing studies, and tech trends. The key: be comprehensive but organized.

Step 2: Build Your Knowledge Vault Convert everything to PDFs. Web pages, Google Docs, research notes. Standardize the format. Include context documents explaining your business model and strategic priorities.

Step 3: Create Your Custom GPT Upload all PDFs to a Custom GPT's knowledge base using these specific instructions: 🔗 Instructions prompt

What This Actually Delivers

Your research assistant becomes your pattern recognition engine, strategic synthesizer, and opportunity spotter. Instead of asking "What are competitors doing?" I prompt:

• "What market opportunities are competitors missing that align with our capabilities?"

• "What feature requests keep appearing that no one's addressing?"

• "What pricing models are gaining traction and why?"

The responses aren't summaries. They're strategic analysis that would take hours to develop manually.

The Compound Effect

Here's what gets interesting: your research assistant gets smarter with every document you add. It's like having an analyst who never forgets and can connect dots across massive amounts of information instantly.

Personal Take: Why This Actually Matters

Most founders either over-research (analysis paralysis) or under-research (gut decisions with incomplete data). This workflow finds the middle path: comprehensive intelligence that drives faster, better strategic decisions.

The real value isn't having an AI that reads for you. It's having a system that thinks strategically about what you've read.

Who's really winning here? Solo founders who understand that strategic advantage comes from better synthesis, not just more information. Stay systematic, and maybe spend less time reading and more time acting on insights.

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💎 Data Gem

74% of SMBs say they plan to increase AI spending in 2025. (Capgemini)

Small and scrappy doesn’t mean slow, nearly three-quarters of small businesses are doubling down on AI this year. Only time will tell, but my bet is even more than 74%.

 📰 What’s Trending

Groks will soon answer… with ads
Elon Musk announces X plans to integrate ads directly into Grok chatbot responses. When your AI assistant starts recommending moisturizers mid-conversation, you'll understand the shift. Win for advertisers? Likely. User experience quality? Remains uncertain.
🔗 Elon Musk Says X Plans to Introduce Ads in Grok’s Responses

Truth Social’s AI search runs on Perplexity, but with handcuffs
The Trump-affiliated platform leverages Perplexity AI for search functionality, though with limitations on source selection. Content curation or information filtering? Regardless, it highlights how AI outputs depend entirely on platform policies.
🔗 Truth Social’s AI Search Is Powered by Perplexity

Google says it’s not killing the web, promise
Amid publisher criticism, Google maintains its AI Overviews aren't causing reduced website visits. Yet if users bypass original sources, who sustains content creation? SEO-dependent business owners should monitor this development carefully.
🔗 Google Denies AI Search Features Are Killing Website Traffic

OpenAI is giving ChatGPT to the government, on the house
OpenAI introduced a program providing heavily discounted, essentially free access to U.S. federal agencies. That represents significant reach, influence, and deployment scale, despite razor-thin profit margins.
🔗 OpenAI Is Practically Giving ChatGPT to the Government for Free

Trump hints at chip tariffs, again
During a recent address, Trump proposed additional chip tariffs designed to rebuild domestic semiconductor manufacturing. For those building AI infrastructure or depending on global hardware pricing, such policy discussions carry real implications.
🔗 Trump Says He’ll Announce Semiconductor and Chip Tariffs

ChatGPT approaches 700M weekly active users 
OpenAI reports rapidly accelerating adoption, nearing 700 million weekly users. That surpasses TikTok's domestic audience. Distribution at this scale transforms minor feature updates into market-moving events.
🔗 ChatGPT Is on Track to Reach 700M Weekly Users

Grok's latest imaging tool permits adult content 
xAI released Grok Imagine, a visual content generator that notably allows mature material. Unlike OpenAI or Google's approach, Elon's team positions "reduced restrictions" as competitive advantage…content creators should proceed thoughtfully.
🔗 Grok Imagine Lets You Make NSFW Content

Anthropic terminates OpenAI's Claude access 
Unexpectedly, Anthropic ended OpenAI's Claude model privileges, concluding a previously undisclosed collaboration. Bottom line: elite AI competition returns to winner-take-all dynamics and inter-company barriers are solidifying.
🔗 Anthropic Cuts Off OpenAI’s Access to Claude

OpenAI secures $8.3B funding at $300B valuation 
SoftBank spearheaded the investment round, elevating OpenAI's worth to an unprecedented $300 billion. This isn't merely venture capital enthusiasm, it's operational capital for computing power, talent acquisition, and market expansion.
🔗 OpenAI Reportedly Raises $8.3B at $300B Valuation

🧠 Custom GPT (sorta)

How I Built My Own Virtual Co-Founder

I don't have a link for you today, that would compromise my latest SaaS idea (there's your hint). But I've unlocked a workflow that's honestly super helpful on so many levels: I've essentially built my own co-founder using AI.

The Problem Every Non-Technical Founder Faces

I'm the marketing/sales guy who has zero desire to learn code. Technical specs make my eyes glaze over, but give me enough research and patience, and I can translate complex tech concepts into strategic messaging that actually converts. I'm the perfect complement to a developer, except finding that developer co-founder is harder than finding product-market fit.

After diving deep into my latest idea, I realized it's super complex, massively underserved from a marketing perspective, and honestly shocked it hasn't been done yet. Classic founder delusion? Maybe. But this time I had backup.

Here's How I Built My Virtual Co-Founder

Step 1: Research Everything Using tools like Manus (and others), I researched:

• Target audience behaviors and pain points

• Competitive landscape and positioning gaps

• Technical logistics and backend requirements

• Market size and opportunity assessment

• Implementation challenges and solutions

Step 2: Create Your Knowledge Base Download all research as PDFs. Every competitor analysis, market report, technical specification, customer interview transcript…everything goes into the knowledge vault.

Step 3: Build Your Custom GPT Upload all PDFs to a Custom GPT's knowledge base, then use instructions like these to create your virtual co-founder: [Co-Founder Instructions Template]

The key? Be brutally specific about what you need: strategic oversight, reality checks, technical feasibility assessment, and someone who'll call out your BS when necessary.

What This Actually Gives You

Your AI co-founder becomes your:

• Strategic sounding board for major decisions

• Reality checker when you're being overly optimistic

• Research synthesizer who knows your entire competitive landscape

• Implementation guide who breaks complex strategies into actionable steps

• Honest critic who won't protect your ego

Personal take: This isn't about replacing human co-founders, it's about having that strategic partner available 24/7 during the crucial early validation phase.

Beyond Co-Founders: Other Applications

This workflow works for any complex business challenge:

• Industry Expert: Upload industry reports, create a specialist consultant

• Customer Success Manager: Feed it support tickets and user feedback for pattern recognition

• Competitive Intelligence: Upload competitor data for strategic analysis

• Investment Advisor: Market research + financial models = informed decision-making

The Real Value

What I'm really building isn't just a virtual co-founder, it's institutional knowledge that doesn't walk out the door, get equity, or have conflicting visions. It's strategic thinking that scales with your research depth.

The most interesting part? The AI gets smarter as your business knowledge grows. Every new piece of research, every customer conversation, every competitive insight makes your virtual co-founder more valuable.

Who's really winning here? Solo founders who understand that strategic thinking matters more than just having warm bodies in co-founder roles. Stay curious, stay critical and maybe stay solo a little longer than conventional wisdom suggests.

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💎 Data Gem

AI adoption among small businesses surged 41% in 2025 so far (Capgemini)

Jumping from 39% to 55% YoY. More than half use AI daily, and 58% report saving over 20 hours a month, which is time they’re reinvesting back into growth.

 📰 What’s Trending

Apple’s AI money cannon is warming up
Tim Cook says Apple’s AI investments are “ramping significantly”—which likely means Siri’s glow-up is coming sooner than we think. Hardware is still king for Cupertino, but AI is the new battleground.
🔗 Apple Plans to Significantly Grow AI Investments

Reddit rides AI + ads to a $240M quarter
Reddit’s Q2 revenue jumped 34%, thanks to licensing content for AI training and shoring up its ad platform. Is everything an “AI company” these days?
🔗 Reddit Revenue Soars as it Bets on AI and Advertising

Anthropic beats OpenAI…at least with enterprise buyers
A new survey shows businesses prefer Claude over ChatGPT for accuracy, transparency, and safety. If you're building for B2B, it might be time to give Claude a serious look.
🔗 Enterprises Prefer Anthropic’s AI Models

Your ChatGPT chats might be turning into blog posts
OpenAI confirms that public ChatGPT queries are being indexed by Google. If you’re using it for SEO research, strategy, or customer work - start thinking like a publisher.
🔗 ChatGPT Queries Are Getting Indexed by Google

Zuck: If you don’t wear AI glasses, you’ll fall behind
Meta’s CEO is doubling down on smart glasses, arguing that those without wearable AI will be at a “disadvantage.” He’s selling the future of productivity like it’s Ray-Bans meets Iron Man.
🔗 Zuckerberg Says People Without AI Glasses Will Be at a Disadvantage

Anthropic’s value jumps to $170B with new funding in the works
Claude’s parent company is reportedly close to locking in another $5B, pushing its valuation near $170B. That’s OpenAI-level territory without the same drama.
🔗 Anthropic Nears $170B Valuation

Spotify wants its voice AI to sound less robotic
Spotify is exploring a more conversational AI interface—think assistant meets DJ meets podcaster. Great for user experience, but also a massive opportunity for content discovery and brand placement.
🔗 Spotify Hints at a More Chatty Voice AI

Robinhood’s CEO launches a math chatbot for humans
Harmonic, a new AI startup from Vlad Tenev, is tackling the gap between people and math. Early bet, but if they pull off a chat-native math tutor, it could crush in edtech and finance.
🔗 Harmonic: Robinhood CEO’s Math Startup

 🤔 The Figma IPO Thing

So Figma's going public and I have thoughts.

I've been using the platform for years. Started out designing terrible mockups myself, then eventually learned to work with actual designers who knew what they were doing. Here's the thing though: every single designer I've worked with uses Figma.

The numbers are pretty wild when you look at them. They went from 4 million users in 2022 to 13 million monthly actives by Q1 2025. But more telling is the market share flip: 7% of designers in 2017, 90% by 2023.

And I get why. The collaboration part just works. I'm literally sharing designs with my email marketing clients directly in Figma. They comment, we iterate, they approve. No more PDF hell or "final_design_v7_ACTUALLY_FINAL.sketch" nonsense.

Here's where it gets weird, though

I have a few friends in central finance and we’ve been discussing the Figma IPO this week leading up to it. Turns out, they didn’t even know what Figma was, they just kept thinking it was an AI company. And I tried to tell them it’s a design collab platform, not an AI company. But then they’d send me stock descriptions and AI overviews from Google which all said "AI-powered platform" this and "AI tools" that. They genuinely thought they were investing in an AI company.

Which is bizarre because Figma's AI stuff feels pretty secondary. They have some AI features rolling out, sure, but that's not why 13 million people use it every month. They use it because it solved the actual pain points of design collaboration better than anyone else.

Maybe Wall Street knows something I don't. Maybe they're betting on what Figma becomes rather than what it is. The company will definitely dump money into AI now that investors expect it. But it feels backwards to me.

Figma already won by fixing real workflow problems. They made design collaboration actually work instead of being a nightmare of conflicting versions and broken handoffs. The AI layer might be nice to have, but the foundation was built on solving genuine day-to-day frustrations.

What happens next

The IPO performance probably depends on whether Figma can do both things well. Keep dominating design collaboration while building whatever AI magic Wall Street thinks they're buying.

For those of us actually using the tool, this creates an interesting situation. We already have something that transformed how design happens. Now we're getting AI enhancements driven more by investor expectations than user requests.

I'm not against AI integration. If they can make the design process even smoother, great. But I hope they don't lose focus on what made them essential in the first place.

Those 13 million monthly users aren't going anywhere regardless. The design world already voted with their workflows.

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💎 Data Gem

Full-scale AI agents will create up to $450B by 2028, but only 2% of organizations are actually doing it. (Capgemini)

That’s right: the market upside is immense, but rollout lags. Organizations that have scaled agentic AI report an average value gain of $382M, compared to just $76M for those in pilot stages that’s a gap worth paying attention to.

 📰 What’s Trending

🔗 White House targets “woke AI” in new executive order
Trump’s latest move bans federal agencies from using “politically biased” models…code for DEI-leaning training data. This could open the floodgates for ideologically skewed LLMs and fracture the model landscape along culture lines.

🔗 Google + OpenAI = Strange bedfellows, smarter stack
OpenAI’s tools are officially landing on Google Cloud, making GPT-4 easier to access for devs already living in GCP. Azure’s grip loosens, and Sundar’s platform suddenly looks friendlier to AI startups.

🔗 Google Photos adds remix mode for your memories
You can now animate old pics, apply stylized effects, or convert images into short video clips. It’s not just nostalgia—it’s a new way to generate brand content from your photo archives.

🔗 YouTube Shorts gets AI upgrades for creators
Shorts now lets you animate images into videos and add smart effects with minimal effort. If your content team’s small (or just tired), this could be the AI assist you’ve been waiting for.

🔗 Hiring AI talent now feels like the NBA draft
PhDs are getting poached with VC money, equity deals, and NFL-level salaries. The AI arms race is real and startups need more than ping pong tables to compete.

🔗 Lovable rockets to $100M ARR right after unicorn status
Fresh off a $1.5B valuation, Swedish startup Lovable just hit $100M ARR in under 8 months. With rankings showing 2.3M active users and 180K paying subscribers, it's clearly bridging the gap between playground projects and business-grade use cases

🔗 Amazon acquires Bee, the mic that never stops listening
Bee is a tiny AI wearable that records every word you say and Amazon just bought it. Expect ultra-personalized shopping, smarter Alexa prompts, and a privacy debate that won’t quit.

🔗 Groq’s AI friends are cool—but now they make money
Groq’s viral AI companion apps drove installs, but it’s the latest version that’s turning revenue. Consumer AI can’t live on novelty alone, this pivot to substance is what keeps users (and investors) around.

 🎥 Behind the Scenes

ChatGPT won by a long shot - not surprised. Personally, I’ve been using Claude a ton especially the “Projects” feature. Will show you my use case below.

Custom GPTs vs. Claude for Client Work

The custom GPTs (featured below) handle technical consulting like pricing structures and AI tool evaluations. But Claude through projects has been exponential for client work: landing pages, email marketing, content creation.

My Process: 

_{Upload everything about the client: business overview, target audience, website link, feedback. Then use Manus.im for audience research (X, Reddit mainly) to capture actual pain points and language patterns. Don't limit Manus to just this. It's solid for any research needs.}

_{Project Instructions (Wireframe Example): You're a conversion-focused copywriter with deep SaaS/tech experience. Goal: drive demo bookings, not pretty pages. Structure as landing page + advertorial hybrid.}

_{Page Flow:}

1. _{Headline + Subhead → Hit the #1 pain/emotional driver}

2. _{The Problem → What's broken now?}

3. _{The Fix → Product as better solution}

4. _{How It Works → Clear steps, no jargon}

5. _{Proof & Trust → Credibility markers}

6. _{Address Doubts → Kill top objections}

7. _{CTA (x3) → Consistent, obvious}

<sub>Guidelines:
- Clarity over cleverness
- Speak to end buyer, not founder
- 1-2 CTAs max
- Include inline suggestions for buttons/visuals
- Clean formatting for no-code builders</sub>

<sub>Context Inserts:
- Audience: [buyer persona]
- Emotional hook: [speed/fear/control/money]
- Pain points: [research findings]</sub>

Then boom…Claude will deliver a killer wireframe. Structure and layout are spot-on even if colors need work. Perfect visual for client alignment before building in Lovable.dev.

That's my current website workflow. Examples coming in a few weeks.

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🧠 Custom GPT of the Week

AI Business Model Validator

Thinking about launching an AI product but not ready to bet the farm?

Before you quit your day job or blow through runway figuring out pricing, test your assumptions with the AI Business Model Validator.

What it does: Takes your rough product idea and stress-tests the economics. Upload your concept, whether it's a specialized GPT, automation tool, or AI-powered SaaS and get realistic projections on pricing, user acquisition costs, and revenue potential.

Why it matters: AI products have weird economics. Token costs compound differently than traditional hosting. Enterprise buyers evaluate AI tools differently than standard software. Freemium conversion rates vary wildly between AI categories.

This GPT understands these nuances. It'll catch pricing model mismatches before you build the wrong thing, validate your target market assumptions, and show you if the unit economics actually work at scale.

Best for: Early-stage founders who want validation before heavy investment, existing SaaS teams exploring AI features, or anyone tired of guessing what their AI product should cost.

Quick reality check before you commit resources. Better than learning expensive lessons in production.

👉 AI Business Model Validator

💎 Data Gem

Marketing teams using AI see a 300% average ROI (CubeIO)

Recent analysis highlights that organizations adopting AI solutions are reporting an average 300% return on investment, driven by higher conversion rates (+40%) and boosted order values (+35%)…all within months, not years

 📰 What’s Trending

🔗 xAI’s safety vibe: Fast, loose, and calling out critics
Former researchers from OpenAI and Anthropic are sounding the alarm on xAI's safety practices—or lack thereof. They say the culture's too reckless, with zero real accountability. If you're building anything with users in mind, this is a case study in what not to copy.

🔗 Lovable proves AI dev tools aren’t just hype
Eight months in, Lovable just landed $200M and a $1.8B valuation for its AI app builder. With real ARR and 180K paying users, it's showing that "vibe-based coding" is more than a gimmick. Personally, this has been my favorite AI tool for months…it’s what no-code should’ve been all along.

🔗 xAI’s new job post: Must love anime, also AGI
Yes, this is real: xAI is hiring someone to make anime “waifus” with Grok. Laugh if you want, but it shows how cultural niches are becoming AI battlegrounds. And how far Elon’s willing to go to own engagement.

🔗 Inside OpenAI’s pressure cooker
A former engineer describes the work culture as intense, ambitious, and kind of unrelenting. Cool if you’re into the whole “build AGI before lunch” vibe, but maybe not if you’re optimizing for health and boundaries.

🔗 Grok 4 gets a filter, but can it earn trust?
After some wild responses, xAI says Grok-4 is now fixed. Technical improvements are nice, but trust takes more than patch notes. Especially when you’re dealing with open-domain chat models in the wild.

🔗 People are finally ditching Chrome
Alternative browsers like Arc, SigmaOS, and Sidekick are surging, many with built-in AI tools. The browsing experience is getting smarter, and for marketers, that means your touchpoints are shifting again. However, all the built-in AI in the world won’t stop me from having 78 different tabs open.

🔗 AI didn’t just join Prime Day, it supercharged it
US e-commerce hit $24B for Prime Day, with GenAI traffic up 3,300 percent. From product copy to price tracking, AI’s now part of every layer of the sales funnel. Congrats to the Ecom fellows who were part of this $24B spending spree.

🔗 AI therapy still can’t do nuance
A recent study flags the risks of using chatbots for mental health support—misdiagnoses, poor advice, even harm. The tools are getting smarter, but empathy isn’t something you can prompt on demand. Brb while I try out Grok’s anime waifu the next time I’m in a fight with my girlfriend.

🔗 CEO bail sinks OpenAI’s Windsurf deal
The CEO of Windsurf bailed for Google, and just like that, its acquisition by OpenAI is gone with the wind. Another reminder that in AI, talent moves faster than the money. And shapes the game just as much.

💡Smart Moves

AI Notetakers Are Quietly Leaking Risk. Audit Yours With This Checklist.

AI notetakers are becoming standard issue in meetings, but most teams haven’t vetted them properly.

✔️ Is AI trained on your data?
✔️ Where is the data stored?
✔️ Can admins control what gets recorded and shared?

This checklist from Fellow lays out the non-negotiables for secure AI in the workplace.

If your vendor can’t check all the boxes, you need to ask why.

Get the Security Checklist

🧠 Custom GPT of the Week

Here's the reality: most people are leaving 70% of AI capability on the table because they're asking the wrong questions. It's not about the model's intelligence. It's about your ability to communicate what you actually want.

I discovered this gap while working on a complex data analysis project last week. Needed to extract specific insights from customer feedback across multiple product lines, but my initial prompts kept returning surface-level summaries. The AI had the capability, but I wasn't providing the structural framework it needed to deliver meaningful analysis.

What this GPT actually does:

• Transforms vague requests into precise, actionable instructions

• Tests different prompt architectures to identify optimal approaches

• Reveals the underlying patterns that consistently unlock better performance

The difference isn't subtle. Weak prompt: "Analyze this data." Strategic prompt: "Extract sentiment patterns from customer feedback, group by product category, identify the top 3 friction points mentioned across segments, and rank solutions by implementation complexity and potential impact."

Same model. Completely different analytical depth.

👉 Try AI Prompt Engineering Master

💎 Data Gem

42% of B2B leaders are actively deploying GenAI in sales and buying processes (McKinsey)

McKinsey’s latest B2B Pulse (Mar 27, 2025) reports 19 percent are already using GenAI and 23 percent are in pilot phase—totaling around 42 percent adoption among decision-makers. That means nearly half of enterprise buyers are being shaped by AI insights and if your product isn’t part of that pipeline, you’re missing a seat at the table.

 📰 What’s Trending

🔗 Grok 4 drops—with a $300/month “Pro” plan
Elon’s xAI just launched Grok 4, boasting GPT-4–level performance and baked into X for power users. The kicker? A $300/month premium tier that includes early features, priority access, and (eventually) agent tools. For startups and creators, it’s a signal: elite AI access is going full-tiered and premium.

🔗 OpenAI is building a browser—and it could be the new Chrome
Word on the street is OpenAI’s launching a standalone AI browser within weeks. Not just a ChatGPT wrapper—this could integrate search, memory, and agents into a single UX. Big implications for SEO, content strategy, and how users discover anything online.

🔗 YouTube to crack down on AI junk content
YouTube is prepping new policies targeting “mass-produced” and repetitive AI videos. Creators flooding the feed with low-effort slop, beware. For marketers, it’s a reminder: quality and originality still win. Algorithm or not, people can smell the spam.

🔗 SaaS might be over—agents are in
Narada AI’s CEO says the old SaaS model is toast. Autonomous agents that handle workflows end-to-end are the future. Founders, take note: this shift could gut entire verticals—or open lanes for ultra-lean startups.

🔗 Perplexity launches Comet, its own AI browser
Following OpenAI’s footsteps, Perplexity just dropped Comet, a browser built around its search assistant. Think real-time answers and a UI made for speed over clicks. If you're building content or running ads, the distribution game might be about to shift... again.

🔗 Apple loses another key AI lead to Meta
Apple’s senior AI scientist has jumped ship to Meta, joining a growing list of talent exits. Not a great look for Cupertino’s AI ambitions. For product leaders, it’s a peek into where top minds think the action really is.

🔗 Tencent unveils benchmark for creative AI
Tencent just rolled out a new benchmark for evaluating creative AI—measuring image quality, originality, and human-likeness. Expect this to influence how tools are marketed and how brands vet AI-generated assets.

🔗 Replit ditches Google Cloud for Microsoft
In a surprising move, Replit is now partnering with Microsoft after snubbing Google Cloud. Big win for Azure’s developer play. For startups, it's a reminder to bet on infra partners that move fast and align with your AI roadmap.

🔗 Cluely hits $7M ARR in a week—but rivals are circling
Cluely, a viral AI productivity tool, doubled its ARR in 7 days. Great headline, but now the clones are coming. The takeaway? Velocity matters, but moats matter more. Build something people love and can't copy overnight.

BONUS: Grok 4 just dropped hours ago and yes, we’ve already got a thread breaking down its best real-world uses.
👉 Check the thread out here.

📊 Poll Results

You all showed up on Tuesday—Marketing & Advertising took the crown by a mile. Now it’s time to zoom in. I’ve pulled together a few standout tools in that space (some I’ve tested, others I’m eyeing). Cast your vote below, the top two will face off next Tuesday.

🧠 Custom GPT of the Week

Ever spent an hour Googling “best AI tools for X” only to end up buried in half-baked lists and outdated Reddit threads? Yeah—same.

Last week, I was trying to find the right AI video tool for a pitch deck and somehow ended up comparing eight tabs, five pricing pages, and one YouTube explainer with a robotic voiceover. Felt like digital archaeology.

That’s why this GPT is a gem. AI Tool Stack Curator helps you discover, compare, and vet AI tools for exactly what you need. Whether you're building a product, revamping your ops, or just curious what's out there, it trims the fat so you can move faster.

👉 Try AI Tool Stack Curator

💎 Data Gem

54% of U.S. SMBs say they’ve adopted at least one AI tool in 2024. (Forrester)

The top reasons? Automating customer support, speeding up content creation, and better decision-making. If your product doesn’t plug into that trifecta, you’re already behind.

 📰 What’s Trending

Google teases “playable” AI with Veo 3
Veo 3 introduces spatial awareness to Google’s video model, letting it understand and simulate environments. This could unlock interactive demos and AR-style product experiences that behave like real life.

Perplexity rolls out $200 pro plan
Its new premium tier includes deeper search tools and custom data sources. If your team relies on AI for research or client insights, this could be a power boost worth budgeting for.

ChatGPT referrals are up, but not enough
AI-driven clicks to news sites are growing but still too small to offset the decline in search traffic. Publishers and content marketers can’t rely on AI alone to drive volume yet.

X tests AI-generated Community Notes
Chatbots are now drafting early versions of Community Notes before human review. If your content trends on X, expect faster, AI-shaped commentary that may influence perception.

Amazon hits 1M robots and launches new AI model
A million robots now run Amazon warehouses, guided by a new in-house generative AI. It’s a preview of the automation coming to mid-market logistics and ecom ops.

Circle wants to build the first AI-native bank
Co-founder Sean Neville shared plans for a fully AI-powered financial institution using smart contracts and USDC. It’s a roadmap for fintech teams looking to ditch manual ops.

Grammarly buys Superhuman
Grammarly acquired Superhuman, blending elite writing assistance with a fast productivity inbox. Expect tools that auto-draft, clean up, and send email while you focus elsewhere.

Apple may give Siri a brain transplant
Talks with OpenAI and Anthropic could finally make Siri conversational and useful. That means voice-first apps could get smarter by default across iOS.

Meta offers AI engineers up to $300M
Zuckerberg is luring top AI talent with equity deals worth up to $300 million. It’s a bold escalation that resets hiring expectations across the entire sector.

💡Smart Moves

If you’re running DTC and tired of watching margin disappear to browser extensions and leaked promo codes, this one’s for you. KeepCart helps brands like Quince, Blueland, and Vessi monitor and block coupon abuse from sites like Honey and RetailMeNot so your discounts stay where they belong.

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🧠 Custom GPT of the Week

SaaS Pricing Strategy Analyzer
When I first offered my marketing services as a subscription, I priced it like a product—one flat rate, take it or leave it. What I quickly learned was that funded startups and scrappy bootstrappers don’t want the same thing. I had to pivot fast, building more flexible tiers based on where people were in their journey.

Since then, I’ve helped SaaS teams untangle their own pricing messes, and every time I wished there was a way to run the numbers before burning ad spend. This GPT is that shortcut. It thinks like a pricing strategist—segments, elasticity, funnel design, even launch timelines. Try it here: SaaS Pricing Analyzer

💎 Data Gem

55% of B2B buyers say they’d pay more for AI-powered support tools. (Forrester)

If your SaaS or service includes helpful AI features, don’t bury them. They’re not just valuable, they’re monetizable. That’s not to say slap “AI-Powered” on your next product, but show how you integrated AI features and how it powers your product, data, automation, business ops, etc.

Happy Wednesday!

Today's matchup: Pictory.ai vs. Veed.io

Both claim to simplify video creation with AI. One leans hard into speed and automation. The other mixes AI flair with classic editing tools. It’s content repurposing vs. creative control.

Let's break it down.

  ⚔️ Pictory AI — Text-to-Video on Autopilot

Pictory's vibe? "Just paste your blog and boom, it's a video."

✅ Lightning-Fast Value Delivery → Zero learning curve. "Create stunning videos in minutes using text" isn't just marketing fluff… it's the actual user experience.

✅ Pain Point Precision → Finally, someone gets it. Content marketers buried under blog backlogs and webinar archives have a lifeline.

✅ Workflow That Actually Works → Upload text. Auto-generate scenes. Minimal tweaking. Ship it. This is automation done right.

✅ Repurposing Intelligence → Highlight extraction, blog-to-video conversion, PowerPoint imports. Your existing content just became a video library.

✅ Niche Mastery → Laser-focused on content marketers, course creators, and webinar recyclers. No identity crisis here.

⚠️ Customization Constraints → Love the defaults? You're golden. Need pixel-perfect control? Look elsewhere.

⚔️ Veed IO — AI Meets Classic Video Editing

Veed's vibe? "Everything you need, without the Final Cut headache."

✅ Approachable UI → Drag-and-drop simplicity that welcomes non-editors instead of terrifying them. Modern interface design that actually makes sense.

✅ Feature-Rich Arsenal → AI avatars, screen recording, timeline editing, dubbing capabilities. It’s like having a little video production studio inside your computer.

✅ Versatility Champion → Social content to L&D training videos. Wide net strategy executed flawlessly across multiple use cases.

✅ Cross-Platform Dominance → That 4.9-rated mobile app? Game changer. Edit anywhere, anytime without compromise.

✅ Conversion Psychology Mastery → Brand logos, strategic testimonials, transparent pricing. They understand trust-building at the molecular level.

⚠️ Feature Bloat Reality → Sometimes having everything means overwhelming everyone. New users might need a roadmap just to find the start button.

Quick Takeaway

If you're staring at a mountain of blog posts, webinars, or course scripts and thinking "I wish this was video," Pictory is your magic wand. It's fast, focused, and nearly frictionless for repurposing content at scale. Ideal for solo content marketers and small teams who don't want to learn video editing.

If you need more creative control while still skipping the Adobe learning curve, Veed delivers. It’s surprisingly robust yet beginner-friendly, making it perfect for marketing teams, social media pros, and L&D folks creating polished, on-brand videos with a mix of AI and manual finesse.

Bottom line:

• Use Pictory if you're repurposing existing text into video with speed.

• Use Veed if you want to produce more diverse video content with flexibility and brand polish.

Both tools make AI video editing accessible—just from different angles. Choose your weapon.