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22 ChatGPT Agents Built for Every Marketing Job

Most marketers use ChatGPT to do general research and then call it an AI strategy. The ones outperforming them are deploying specialized agents built for specific jobs.

We put together 22 plug-and-play ChatGPT marketing agents that handle the work eating your week, each with built-in instructions and structured outputs ready to go in under 5 minutes.

Subscribe to Marketing Against the Grain and get all 22 free.

Inside you'll find:

• Competitive intelligence agent that visits competitor websites and builds detailed comparison matrices automatically

• Customer feedback analyzer that ranks improvement opportunities by business impact

• Social listening specialist that monitors brand mentions and flags reputation risks before they escalate

• Campaign optimization agents that handle attribution analysis and surface what is actually driving results

Your competitors are already running agents like these.

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Step 1: Pick the Most Obvious Niche in Your Life, Not a Clever One

When I say niche, most people freeze. They think they need a hidden market nobody has found. That is wrong.

You need a niche where three things are true. The audience has a problem they are trying to solve right now, not someday. They already spend money trying to fix it. And the problem is emotionally loaded. Shame, frustration, fear.

Boring problems beat exciting problems every time, because boring problems are the ones people are quietly desperate to fix.

Will was an Uber Eats driver. No audience. He picked productivity for busy professionals because he was one. He knew what people Googled at 11pm when the day got wasted. He made $8,000 in two weeks.

Matt had a normal 9 to 5. He built a product on how to make friends as an adult. Sounds like nobody would pay for that. He sold it for $1,000 a unit and made $7,000 in 30 days. Because nobody talks about that problem, but everyone feels it.

One test. Are people in this niche already paying to solve this? If yes, it works. If they pay for nothing, walk away.

Step 2: Find One Specific, Painful, Named Problem

This is where most people mess up. They pick a niche, then try to solve every problem in it. The product ends up generic because it is.

You need one specific problem. Not "I help people be more productive." Try "I help busy parents stop losing two hours a day to phone scrolling."

To find it, go where your audience already complains out loud. Reddit threads. Facebook groups. YouTube comments. Amazon one-star reviews, because that is where people say what the book did not solve. You are looking for the same complaint coming up over and over. See it 15 times in a week, you found something worth solving.

My five-minute test. Open a notes app. Set a timer. Dump out every problem your audience deals with. When it hits, circle the three written in the most emotional language. "I hate." "I cannot stand." "I am desperate."

Emotional language is buying intent. People pay to fix problems that are eating them alive, not problems they feel mildly about.

Step 3: Validate It Before You Build a Single Thing

This is the step almost everyone skips, and it is why people waste months building things nobody wants.

Validation is one question. Will somebody actually pay for this?

Two tests. The dollar test: can the person put a real cost on this problem? Missed promotions. Lost sleep that hurts their work. If they can attach a dollar figure, they will pay to fix it. The "already paid" test: have they spent money trying to fix this before? Books, apps, coaches. If they opened their wallet once, they will again.

But validation does not happen in your head. Talk to real humans. Ask three questions. What have you already tried? How much time have you spent? What is the most painful part?

Five people giving specific, emotional, dollar-attached answers means you validated it. Five shrugs means go find a better problem.

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FAQs. Comparison pages. Transparent pricing. LinkedIn presence. These aren't vanity plays. They're what gets you cited in ChatGPT, Gemini, and Claude when your buyers are researching, your investors are looking, and your future hires are deciding where to work.

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Step 4: Sell the Offer Before You Build the Product

Here is where I want to be direct, because I have watched this play out a thousand times.

The person who struggles builds first, then prays. Three months on a course. A logo. A fancy website. They launch. Then they watch the silence.

The fastest operators flip it. They sell the offer first, before it exists. Then they only build when people pay.

Take the problem you validated. Write one pitch. Describe the problem in painful detail. Describe the outcome. Give the offer a name. Put a price on it. Then put it in front of people. No audience? Text five people in your phone. Email ten on your list. No product. No 12-page website. Just one clear offer and a payment link.

Say you validated that busy parents lose two hours a day to scrolling and hate themselves for it. Your offer is "The 7-Day Phone Detox for Parents." Delivered as a step-by-step guide with daily check-ins. $27 or $47. You do not pretend it exists yet. You put "delivery in 7 days" on the confirmation. People pay for the outcome, not the file.

This is not a gray area. Every Kickstarter works this way. Every pre-order works this way. It is called an MVP. If three people pay you $47, build it. If nobody pays, go back to Step 2. The risk is essentially zero.

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Step 5: Build It With AI the Right Way (Most People Use It Wrong)

Now the part everyone thinks is hard. It is not. But almost everyone uses AI wrong here.

The biggest mistake is using AI to write the product. You type "write me a 10,000 word ebook on productivity" and get a wall of generic content that sounds like every other ebook. Then buyers feel ripped off.

The reframe: the best operators do not use AI to write the product. They use AI to understand the audience. That distinction is everything.

AI does three jobs well. Audience research: feed it every Reddit thread and validated conversation from Step 3 and ask it to find the patterns. What words do people use? What have they tried and rejected? Structure and outline: tell it the problem and outcome, ask it to map the sequence of what someone needs to learn first, second, third. First drafts of connective tissue: you write the parts that need real expertise, your stories and frameworks, then let AI draft the definitions and transitions, which you rewrite in your own voice.

Do it this way and you build a high-quality product in a week, not three months. AI is a research and structure machine, not a writing machine. The moment you internalize that, everything changes.

The Move That Ties It Together: Let Results Sell for You

The last move is delivery, and this is where most people get sloppy. They think the work ends at the sale. It ends when you have a happy customer who got a real result and sends referrals.

Your first 10 customers are not customers. They are your case study factory. You over-deliver. You check in. You collect their wins. A screenshot. A voice memo. A video.

Remember the mentor in my story? He saw a product in my head I could not see. Your job is to do that for your customers. Notice the wins they are not noticing. Once you have three or four real, named results, you have everything you need to attract the next 100 buyers without convincing anyone.

Priscilla, a stay-at-home mom, built a product helping faith-based women earn with TikTok Shop. She showed her first customers' results. The next 100 signed up because the proof was undeniable.

Over $300,000 in lifetime sales. Sean, a full-time nurse, built a product helping people recover after toxic relationships. He showed real results. The next ones begged to sign up. Over $250,000.

These are not gurus. They are normal people who picked a real niche, found a real problem, validated, sold first, and let AI do the heavy lifting.

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First, two ways to start. Only one of them works.

The first way is what almost everyone does. You sit down, you think about what you would love to build, your hobby, your passion, and you build it. Then you go hunting for people who might want it.

This is the creation first path. It is also the slowest, most expensive, most likely to fail way to start anything.

The second way is the opposite. You look at the market first. You find a topic where people are already paying, already searching, already buying from somebody. Then you build your version for that audience.

The market tells you what to sell. AI helps you build it faster than anyone else can.

Proven demand beats original ideas every single time. Hold onto that line. It is the whole game.

Step 1: Pick a niche the market already pays for

Do not start with what you love. I will say it again. Do not start with what you love. Start with what people are already buying.

Open Instagram. Open YouTube. Open Etsy or Gumroad. Type a few keywords into the search bar and look at what is actually selling. Productivity. Fitness. Relationships. Money. Mental health. Side hustles. AI tools. Faith. Self development.

These are evergreen niches. The demand never stops.

You do not need to be the world's leading expert. You need to be one step ahead of the person you are selling to. A college freshman can write a study guide for high schoolers. Someone who lost 20 pounds can teach someone who wants to lose the same 20.

Step 2: Find the specific pain inside that niche

This is where most people get stuck. They pick fitness, then try to sell a generic ebook called "How To Get Fit." Nobody buys that. There is no problem in that title.

Nobody wakes up at 11pm on a Tuesday and types "how to get fit" into Google because their life is on fire. They type "how to lose 15 pounds before my wedding in 8 weeks."

That is a specific pain. That is a product that makes money.

So go where the audience already is and read what they say. The comment sections of the biggest videos in your niche. The Reddit threads where they vent. The three star Amazon reviews of the books they already buy, because that is where people tell you exactly what is missing.

The same complaint will surface again and again. That complaint is your product.

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Step 3: Build it with AI in a single afternoon

This part used to take months. It now takes hours.

Open Claude or ChatGPT. Paste in the pain point you found. Tell the AI exactly who the customer is, what the painful problem is, and the specific outcome they want. Then ask it to write a 5 to 10 page guide that solves that problem step by step.

The first draft will not be perfect. That is fine, because you are not publishing the first draft. You are editing it. You are adding your own voice. You are dropping in the one or two original ideas only you have. You are stripping out anything that sounds generic.

Use Canva for the cover. Export a clean PDF for the file. Price it between $27 and $47. Not $9, because too cheap signals low quality.

Not $297 either, because you have no testimonials yet. That middle range is the sweet spot where buyers do not think twice and you still keep a real margin.

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Step 4: Drive traffic with content that matches the pain

You do not need to be a content creator. You do not need 100,000 followers. You do not need to learn video editing.

You need short, simple content. 7 second videos on Reels, TikTok, Shorts, that speak directly to the exact pain your product solves.

If your product is about waking up at 5am without feeling destroyed, your content is about waking up at 5am without feeling destroyed. Not "morning routines" in general. The specific pain.

Two things happen when you do this. The algorithm shows your content to the exact people who have that pain. And those people self qualify, so by the time they click the link in your bio, they already know they have the problem and suspect you have the answer.

And you never have to show your face. AI avatars, screen recordings, voiceovers. A friend of mine runs a faceless brand built around an AI monk avatar and makes over $80,000 a month selling simple $50 ebooks. The human behind it has never once shown his face.

The platform does not care who the face is. The customer does not care. The only person who cares about your face is your own ego, and that is a problem for another day.

Step 5: Validate before you build anything

Before you write a single page, validate. There are two ways and you should do both.

The first is the AI listening pass. Pull 50 to 100 comments from the top videos in your niche. Screenshot them, drop them into Claude, and ask it to find the most painful repeated problems.

AI reads hundreds of comments in seconds and hands you back the exact words your audience uses. Those words go straight into your title, your sales page, and your content.

The second is the demand signal rule. Find accounts in your niche with a few thousand followers. Look for posts that pulled at least double the views of the follower count. An account with 5,000 followers and a post with 10,000 views is a demand signal.

The algorithm is rewarding that exact content because the audience clearly wants more. Pull 5 to 10 of those, find what they share, and there is your product.

Do all of this before you write one page. The validation is free. The creation is what costs you. Thirty minutes of reading comments saves you three months building something nobody wants.

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22 ChatGPT Agents Built for Every Marketing Job

Most marketers use ChatGPT to do general research and then call it an AI strategy. The ones outperforming them are deploying specialized agents built for specific jobs.

We put together 22 plug-and-play ChatGPT marketing agents that handle the work eating your week, each with built-in instructions and structured outputs ready to go in under 5 minutes.

Subscribe to Marketing Against the Grain and get all 22 free.

Inside you'll find:

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• Customer feedback analyzer that ranks improvement opportunities by business impact

• Social listening specialist that monitors brand mentions and flags reputation risks before they escalate

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Your competitors are already running agents like these.

Get 22 ChatGPT Marketing Agents free when you subscribe to Marketing Against the Grain today.

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1. The chatbots (and which one for which job)

Here is the assumption I have to kill in almost every training I run. People think ChatGPT, Gemini, and Claude are basically the same, so it does not matter which one you grab. That is wrong, and using them randomly is a bad strategy.

Each one has a job.

Claude is your writer. It produces better first drafts, the writing sounds more human, and you need fewer revisions. Feed it samples of your own work and it matches your voice, so the output actually sounds like you.

I use it for presentations, emails, and proposals, anything where tone matters as much as content. If you vibe code, it also writes working code on the first try more often than anything else I have used.

Gemini is your Google brain. If you live inside Google Workspace, this is the one. It has a huge context window, so you can drop in a long video, a giant slide deck, or a massive client request and it handles all of it. It also digs through long Gmail chains and buried Drive files to find that one thing you half remember.

Pick the right chatbot for the right job and you get the right result the first time. That alone saves hours of redoing work.

2. Perplexity (your accuracy layer)

Perplexity is the specialist I pair with my everyday chatbots.

It is built to find accurate, source based information, the kind that general models sometimes hallucinate.

So when my work needs verified facts, like a client research report or background for an interview, Perplexity becomes a second layer of checking on top of whatever ChatGPT or Claude gave me.

One tip. If you want to limit your research to a single source, you can prompt it to narrow down to just that one source. It keeps the answer clean and grounded.

3. Whisperflow (talk instead of type)

I will admit it. I ignored voice to text for years. Every version I tried felt like more trouble than it was worth, and I always ended up back at my keyboard.

Then I tried Whisperflow out of pure desperation. I wanted to fire off a reply to my team while chasing my very active daughter around the playground.

The math is what got me. We speak around 200 words a minute and type around 50. That means I produce writing four times faster just by talking.

Notes, replies, even AI prompts that would have taken forever to thumb out.

The part I love is that it does not just transcribe, it cleans as it listens. Change your mind mid sentence, fumble a word, or say "um" ten times while thinking out loud, and it figures out what you meant. What comes out the other side is clean, coherent text. Now I cannot get through a day without it.

By the way, I put together a free AI playbook with links to my favorite AI tools to help you build your own workflow from scratch. It covers the tools, the prompts, and the systems I actually use. Grab your copy in the link at the bottom.

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4. Gamma (design without being a designer)

Gamma was built by a founder who was not a design person stuck making corporate presentations. That is me. That is most of us.

There is a design tax most people pay without realizing it. You build a great pitch, the design is weak, and the idea does not land the way it should, because we judge the quality of thinking by how it looks on the slide. That is just human nature.

Great design takes time, skill, and tools most people were never trained on. Gamma removes all three.

I hand it my website and branding, and it designs a full, consistent, genuinely good looking deck, faster and better than I could do by hand. If you have ever lost an evening to slide formatting, this one buys it back.

5. NotebookLM (research that never lies to you)

Here is something nobody talks about enough. We live in the most information rich moment in history, and most of us are drowning in it.

I am curious by nature. I read, I listen to podcasts, I save articles. But when I actually needed that one useful framework from a podcast six months ago, it was buried across notes, tabs, and saved links.

inding it took longer than starting over. And even when I found the source, asking a general chatbot about it gave me a confident answer with no way to verify it was real.

NotebookLM fixes exactly this. You upload your own sources, PDFs, YouTube videos, articles, research papers, your notes, and it only answers from what you gave it.

It does not invent a statistic that sounds reasonable. It stays inside your material and cites exactly where each answer came from, so you can check everything.

Then it goes further. It can turn your research into a quiz, a structured summary, a mind map, even a podcast with two AI hosts discussing your notes.

I use that on long research sessions, and it is one of the best ways I have found to actually retain information instead of just consuming it.

When accuracy matters more than speed, this is the tool.

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6. Granola (meetings without the bot)

Let us talk about meetings. Most of us spend a huge chunk of the week in them, half listening while half scribbling notes, and end up with neither good notes nor a clear memory of what was decided.

Most meeting tools try to fix this by sending a bot into your call. That is my biggest pet peeve. You have been in the meeting where an uninvited bot joins and everyone gets annoyed.

Granola works differently. It uses your system audio to capture the meeting in the background. No bot. Nobody knows it is there.

You can jot rough notes if you want, and afterward Granola merges your notes with the full transcript into something structured and actually useful.

The use cases stack up fast. A salesperson can turn the transcript into a follow up email with every detail from the call already in it. And the best part is what it gives back in the room. You get to be present in the conversation again.

Pro tip. Connect Granola to your everyday AI assistant through a connector, and at the end of a meeting it can push the next steps into a task manager like Notion or Asana without you lifting a finger.

7. Google Nano Banana Pro (visuals in plain English)

This last one is for anyone working with images. It cuts your production cost and time hard.

Some of you are wondering why not Midjourney. Midjourney is amazing if you are technical. But for most people, Nano Banana Pro is far easier to start with.

I use it for content visuals that go alongside my videos and posts, infographics, whiteboards, and images for LinkedIn.

What makes it different is precise editing in plain English. No special syntax, no hours tweaking parameters. You describe what you want and it delivers.

Not right? Iterate. Say remove the background, change the color, make it more minimal, and it adjusts. The result comes out photorealistic.

Pro tip. If you need a 4K high resolution image, you can access Nano Banana Pro through Google AI Studio and buy extra credits to download at the settings you want.

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22 ChatGPT Agents Built for Every Marketing Job

Most marketers use ChatGPT to do general research and then call it an AI strategy. The ones outperforming them are deploying specialized agents built for specific jobs.

We put together 22 plug-and-play ChatGPT marketing agents that handle the work eating your week, each with built-in instructions and structured outputs ready to go in under 5 minutes.

Subscribe to Marketing Against the Grain and get all 22 free.

Inside you'll find:

• Competitive intelligence agent that visits competitor websites and builds detailed comparison matrices automatically

• Customer feedback analyzer that ranks improvement opportunities by business impact

• Social listening specialist that monitors brand mentions and flags reputation risks before they escalate

• Campaign optimization agents that handle attribution analysis and surface what is actually driving results

Your competitors are already running agents like these.

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Rule 1: Name the output, not the task

Do not say "review this contract" and pray. Spell it out. "Review this contract. Flag risks per clause. Rate severity 1 to 5. Return as a table." You get structure because you asked for structure.

Rule 2: Cap the length yourself

Saying "summarize this" on a 40 page report lets the model decide how long the answer should be. Box it in. "5 bullets. Each under 15 words. Start each with an action verb." You set the size, not the input.

Rule 3: Flip every negative into a positive

Telling Claude "do not use jargon, do not be salesy" does not stick. State what you DO want instead. "Write in plain English a 16 year old could read aloud." Positive instructions land. Negative ones slip.

Rule 4: Make every verb ship something

"Can you help me with the email?" is too soft. Turn it into a chain of actions. "Go to Gmail. Find the contact. Write the send ready reply. Under 90 words. Tone: confident, casual." Every verb does work.

Rule 5: Force the web search

Here is a detail I did not know. Claude 4.8 calls fewer tools than 4.6 did. So you have to push it. "Use web search aggressively. Verify every claim with at least 2 sources." If you do not push, it will answer from memory.

Rule 6: Feed it your voice

4.8 is direct, with almost zero emojis. If you miss the warmer old tone, do not complain about it. Paste 2 or 3 sentences written exactly how you sound, then tell Claude to match the rhythm. Save those sentences. Reuse them forever.

Rule 7: Ask it to go further

When you request "a landing page," you get the bare minimum. There is one line pulled straight from Anthropic's own doc that fixes this. "Go beyond the basics." Drop it on every creative task and watch the output change.

Rule 8: Turn on thinking

This one surprised me. Claude 4.8 does not reason by default. Add this to the end of your prompt. "Think before answering (maximum reasoning)." It is a free quality upgrade, every single time, and most people never use it.

Rule 9: Build a skill from repeat prompts

If you are rewriting the same prompt 14 times a week, stop. A skill is a command with the instructions already built in. Write the same prompt twice? Make it a skill. Future you will thank present you.

Rule 10: Spell out everything

This is the rule that ties it all together. Old Claude guessed. New Claude does exactly what you typed. So define your output, your order, your length, your tone, your format. If you do not say it, you do not get it.

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Why this list actually matters

Look at all 10 rules together and one theme shows up.

Every single one traces back to the same behavior change. Claude 4.8 stopped filling in the gaps for you.

That sounds like a downside. It is not.

It means you finally get predictable output. The lazier your prompt, the more you are gambling. The clearer your prompt, the more the model just does what you asked. Specificity is the whole game now.

We spent years training ourselves to write loose prompts and let the AI guess. With 4.8, that habit costs you quality on every single request.

Tightening up how you ask is the highest leverage skill in AI right now. Not a new tool. Not a secret model. Just clearer instructions.

If you steal only three things from this list, make it these. Add "Think before answering (maximum reasoning)" to your next complex prompt. Replace one negative instruction with a positive one today. Define your output format upfront, whether that is a table, five bullets, or a word count.

Try them on something boring. Cleaning up an email. Summarizing a doc. You will feel the difference inside one prompt.

Stay curious, talk to you tomorrow.

CoolDeep AI
Helping you stay ahead with AI & productivity

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Most marketers use ChatGPT to do general research and then call it an AI strategy. The ones outperforming them are deploying specialized agents built for specific jobs.

We put together 22 plug-and-play ChatGPT marketing agents that handle the work eating your week, each with built-in instructions and structured outputs ready to go in under 5 minutes.

Subscribe to Marketing Against the Grain and get all 22 free.

Inside you'll find:

• Competitive intelligence agent that visits competitor websites and builds detailed comparison matrices automatically

• Customer feedback analyzer that ranks improvement opportunities by business impact

• Social listening specialist that monitors brand mentions and flags reputation risks before they escalate

• Campaign optimization agents that handle attribution analysis and surface what is actually driving results

Your competitors are already running agents like these.

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It Starts With A Brand Brain

The whole thing falls apart without memory. A tool that forgets your brand every time you open it is just a faster way to make generic content.

This is why the first move matters. Google rolled NotebookLM right into the Gemini app. So you build one notebook that holds everything. The hero products. The customer insights. The product images. Think of it as a brand brain that keeps expanding.

For the demo, the brand was a snack company called Healthy Crunch. Everything I describe below pulls from that one notebook.

Here is the part that clicked for me. Because the product images live inside the notebook, every asset Gemini generates later comes out on brand automatically.

You are not re-explaining your brand on every prompt. You explain it once, and the whole system remembers.

Blog Posts That Build Themselves

First task was a blog post. But not the lazy way.

You attach a content brief skill, and Gemini follows your exact brief template using the notebook as the source. Then you flip on canvas mode and ask for the full post. Out comes a complete article with proper formatting and internal linking already done.

Then it gets better. Turn on image mode and ask for a feature banner plus two supporting images. Because the product images are in the notebook, the visuals come out on brand, featuring the actual product. One click exports the whole thing to Google Docs, visuals included, ready for your team to comment and collaborate.

The same notebook also spits out a lead magnet PDF, like a lunchbox planner for parents. Or an internal one-page retail line sheet for your sales team. Less than ten minutes each.

Nano Banana Is The Quiet Star

You already saw Nano Banana make those blog visuals. On its own it does far more.

Pick image mode and you get pre-built styles. Hand it a few product images, pick a style, and ask for a product ad shot. The first draft is genuinely impressive even with a lazy prompt.

But the real magic is iteration. Ask for a website hero banner. Want to remove a product in the middle? Circle it with the sketch tool and ask. Nano Banana understands the instruction and keeps going until the shot is right.

Three things I want you to steal here:

It does A/B testing for you. Give it a product image and ask for three text-to-image prompts with different backgrounds, moods, and styles. Pick the one you like and generate. Endless campaign angles on demand.

It resizes creatives. A square ad that needs to become vertical for another channel takes about ten seconds. Same concept, new ratio, everything consistent. This one will save you hours.

It never starts from a blank page. Every asset begins from a draft, not from nothing.

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Build It Once, Reuse It Forever With Gems

Here is the catch with everything above. You have to prompt it every time. That gets old fast.

So you build a Gem. A custom Gemini loaded with your brand and workflow once. Give it a name, write the instructions, set the default tool, and attach the knowledge.

The example was a Studio Ad Shot Gem. Default tool set to Nano Banana. Knowledge included the product packaging dimensions, which is a small detail that makes a big difference, because now the model knows your real product size and generates more realistic images. Add a style guide. Attach a notebook.

Now every ad shot comes out consistent, and you can share the Gem with your whole team. One Gem for studio shots. One for lifestyle images. One for campaign copy. Your team stops rewriting prompts and starts working from a standard.

Now The Video Gets Serious

Google has the strongest video model out there, and the new Omni model takes it further. It takes almost any input and generates almost any output, with strong physics and real-world reasoning. Product videos, reels, shorts. Most of what a marketer needs.

Pick video mode, choose a style, drop in a few images. I asked for a product video with a female model holding the snack. Up to ten seconds inside the Gemini app.

The character consistency floored me. It really was the same person the whole way through. And you can change the scene with a prompt while keeping everything else locked, like Nano Banana but for video.

One rule that saves your quota. Plan the storyboard first. There is a Gem that generates an Omni video storyboard using the official prompt guide, scene by scene, and then renders a storyboard image so you can adjust before you ever spend a generation.

Upload those storyboard frames as raw input and the final output is far more predictable.

Omni can even reference video. Feed it a ten-second Instagram reel for pacing and editing style, hand it the product, ask for a recipe reel with real instructions, and it gets the steps right. Complex task, correct output.

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Flow Wraps A Studio Around It

The frustration with video in the Gemini app is real. A few generations a day, no timeline, no editor, no way to connect clips. That is exactly where Google Flow comes in.

You create a brand character once with a reference image and a prompt, give it a name and a voice, and reuse it across everything. Tag the character, tag the product, generate. Strong consistency, real-looking product, almost perfect on the first draft.

Flow also has an agent mode. Turn it on, hand it a product, and ask for three ad variations with different camera moves and angles. The agent asks for your approval, then orchestrates all three generations for you. It follows storyboards too, and the quality almost always comes out better when it does.

The Tool That Does It Without You Driving

Everything so far still needs you in the driver seat, prompt by prompt. Pomelli is the one that drives itself.

You give it your website. It pulls your brand straight off the page and sets up your business DNA. Colors, taglines, catalog, assets, all collected automatically. Healthy Crunch again for the demo, and it grabbed most of the product assets from the site on its own.

Then you create campaigns two ways. Use a pre-built campaign it suggests, like a World Chocolate Day set with on-brand creatives ready to tweak. Or use the chat box.

Pick a few products, give it the offer and the goal, choose the aspect ratio, and it writes a creative brief just like you would plan a real campaign. Confirm, and it generates every asset, on brand, product front and center.

It does photoshoots from your existing product assets. It even builds a simple website from your brand context that you can publish in one click, good enough to test a campaign idea fast.

I walked away genuinely impressed. A free tool that hands you creative inspiration and on-brand assets in minutes.

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What An AI Agent Actually Is (In Plain Words)

Forget every definition you have read. Here is the only one that matters.

An AI agent is Claude doing multiple steps automatically, instead of you doing them one at a time.

Think about how you normally use Claude. You ask it to research something. You read the result. You ask it to write an outline. You check it. You ask it to write the full piece. You edit it. You ask it to format it. You copy it out.

That is four separate tasks. Each one needs you to read, approve, and type the next instruction by hand.

An agent does all four in a row, on its own. You say "research this topic, build an outline, write the full article, and format it for publishing." Claude runs all four steps back to back and hands you the finished result.

That is the entire difference. A normal chatbot does one thing and waits for you. An agent does a sequence of things and delivers a finished output.

Once that clicked for me, I felt silly for being scared of it for so long.

You Do Not Need The Technical Stuff

This is the part that kept me stuck, so I want to kill it early.

You do not need the API. You do not need an Agent SDK. You do not need to write a single line of code.

You can build three kinds of agents using only the tools already sitting inside Claude:

The first is a Chat Agent, built inside Claude Projects. You write a system prompt that defines a full workflow, and every time you give it a task, it runs that whole sequence automatically.

The second is a File Agent, built inside Claude Cowork. It reads a folder on your computer, processes each file, and creates organized outputs from one instruction.

The third is a Scheduled Agent, also in Cowork. It runs on its own on a schedule. It wakes up at 7am, does a job, and saves the result before you even open your laptop.

We are going to build all three. Starting with the easiest.

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Build 1: The Research-To-Article Agent (15 Minutes)

This is a Chat Agent. You give it a topic, it gives you a finished article. One input, one output.

Step 1: Create a new Claude Project. Open Claude. Click Projects. Click "Create Project." Name it "Article Agent."

Step 2: Write the system prompt. This is the brain of the agent. Paste this into the project's system prompt field:

Step 3: Test it. Open a new conversation inside your Article Agent project. Type one thing: "AI agents for beginners."

Claude runs all five steps. Research, angle, outline, full draft, quality check. You get a complete, polished article from a three-word input.

That is your first agent. It took 15 minutes to set up, and it replaces two to three hours of manual work every single time you use it.

The first time I watched it run all five steps without me touching anything, I actually laughed out loud. That was the moment the fear disappeared.

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Build 2: The File Processing Agent (15 Minutes)

This one is a Cowork Agent. It chews through a whole folder of files for you.

Step 1: Open Claude Desktop and go to the Cowork tab. Grant Cowork access to the folder you want to process.

Step 2: Give it a batch instruction like this:

Claude reads every PDF in the folder. Summarizes each one. Creates individual files. Then builds the master document.

One instruction. Entire folder handled. If you have 20 PDFs sitting there, this just saved you an afternoon of reading and note taking.

Build 3: The Scheduled Morning Agent (15 Minutes)

This is the one that genuinely feels like magic. It runs on its own, every morning, before you wake up.

Step 1: Open Cowork.
Step 2: Type /schedule.
Step 3: Configure the recurring task:

Set the schedule. Every weekday at 7am.

From now on you wake up to a full daily briefing. Emails sorted. Replies drafted. Calendar laid out. The agent did the work while you were asleep.

How To Make Your Agents Better Over Time

Your first version of any agent will be good. Not perfect. Here is how you sharpen them.

The Correction Rule. Every time an output needs fixing, turn that fix into a rule in the system prompt. "The summaries are too long" becomes "Each summary must be under 100 words." After ten corrections, your agent is dramatically more precise.

The Example Rule. Upload examples of great output into your Project knowledge files. Tell it "match this standard." Agents with examples beat agents with only instructions, every time.

The Feedback Loop. Once a week, review the past 7 days of output. What worked. What needed fixing. Update the instructions. An agent that gets weekly refinement produces far better work after a month than one that never gets touched.

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Level 1: Unacceptable

This one is obvious. You are not using AI at all.

No ChatGPT. No Claude. No Gemini. Nothing. You are doing every task by hand the same way you did it in 2019.

There is no judgment here, but there is no future here either. If this is a teammate, this is the person you have to worry about. If this is you, the good news is the next level is one tab away.

Level 2: Capable

This is where most of the world lives right now.

You open ChatGPT or Claude. You ask it questions. You use it to search, to draft an email, to summarise an article. You believe in it a little. It saves you a few minutes here and there.

This is good. This is real progress. But here is the trap. Level 2 feels like the destination. It is not. It is the front door. You are talking to one tool, one question at a time, and then closing the tab. You are getting maybe 5 percent of what is actually available to you.

The reason this matters is a number that should bother you. Only 9 percent of companies are actually scaling with AI right now. The other 91 percent are sitting at level 2, poking at ChatGPT, calling it transformation. Almost nobody is shipping. That is not a technology problem. The tools clearly work for some people. It is an implementation problem. And implementation is exactly what the next two levels are about.

Level 3: Adaptive

This is where it stops being a chatbot and starts being a system.

At level 3 you are not asking one off questions anymore. You are building end to end workflows. Let me make that concrete, because the phrase sounds bigger than it is.

An end to end workflow is just three steps. A human gives an input. The AI does the thinking in the middle. The human reviews the output. That is it. Most of the work you do every day is already a workflow like this. You are just doing the middle part by hand.

Once you see that, you start stacking these workflows together. And when you stack enough of them around one job, you get a specialist agent.

One agent that is good at SEO. One that is good at email. One that is good at ad creative. You stop using a generic assistant and you start building specialists that go deep in one area.

The shift in how it feels is enormous. One person we work with described going back to normal work after this as drinking soup with a fork. It technically functions. It just does not work. Once you have specialist agents running your repeat tasks, doing it the old way feels exactly like that.

Level 4: Transformative

This is the top floor. This is closed loops.

For most of history we humans worked in open loops. Hey Bob, how is that report going. Hey Mike, how are the paid ads doing. Hey Anna, where are we on the creatives. Constant checking in. Nobody enjoys it. Nobody wants to be chased and nobody wants to do the chasing.

A closed loop removes the chasing. It is a set of tasks where agents do the work, check each other, and improve over time without you standing over them. You point a human at the top to manage the loop, and the loop runs.

Here is a real example of what that looks like. You can now tell one agent to look at your ad account, double down on the creatives that are working, spin up 200 variations of them, and kill the campaigns that are dead. Work that used to take 2 weeks gets compressed into about 2 seconds. That is the whole game. You are not saving time anymore. You are compressing it.

So the org chart of the future is simple. Humans at the top. Specialist agents below them. Closed loops connecting the agents. If your team is built that way, it compounds. If it is not, it stalls.

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How to actually climb. Three moves by Friday.

Theory is nice. Here is what to do this week.

First, pick one workflow that repeats every single week and gives you the largest return. You know what it is. The annoying thing you do every Monday. That is your first target.

Second, map it as the three steps. Human input. AI thinking. Human review. Write it down literally like that. Most people skip this and that is why their AI use stays stuck at level 2.

Third, build that one workflow and run it for a week. That is the light bulb moment. Once one repeating task runs without you, you will never look at AI as a search box again. Then you build the second one.

You do not need a course. You do not need to be technical. I am not technical and I just like nerding out on this stuff.

The people winning with AI right now are not smarter than you. They are just earlier than you. They started before they felt ready.

The brain you build for yourself first is what you eventually hand to your whole team. One human plus five agents is a 10x team member. Maybe more. But it starts with one workflow, this week.

Start climbing. You are closer to level 4 than you think.

Stay curious, talk to you tomorrow.

Stay curious, talk to you tomorrow.

CoolDeep AI
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• Customer feedback analyzer that ranks improvement opportunities by business impact

• Social listening specialist that monitors brand mentions and flags reputation risks before they escalate

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Level 1: Pick One Model and Go Deep

This is where I made my first big mistake. I tried to learn every AI tool at once.

Do not do that.

Here is why one is enough. The top models used to be far apart in capability. Today they are clustered so close together that the difference for the average user is negligible. And because every AI company copies every other AI company, they all share the same core features. Projects, memory, file uploads, connectors. Learn them once, and the skill carries straight over to the rest.

So which one do you pick? Realistically, you have three serious choices: ChatGPT, Claude, or Gemini.

Use these three principles to decide:

Principle 1: Prioritize paid tiers. If you are on free ChatGPT but your job gives you paid Gemini, go deep on Gemini. The gap between free and paid is night and day. Do not learn AI on the weakest version of it.

Principle 2: Match the AI to your work. ChatGPT is the most mature, has the most tutorials, and is excellent at web search and research. Claude is the strongest at writing, design, and coding, and coding matters even if you are not technical because data analysis and diagrams all run on code under the hood. Gemini is the pick if you work across text, images, audio, and video, or if you live inside Google Workspace.

Principle 3: Vibes. I know it sounds unserious. It is not. Each AI has its own personality, and the more you enjoy using yours, the more you will use it, and the better you will get. Switching later is easy anyway. All three now have memory import features.

One more thing, and this single tip is worth the whole email.

Change your default model. Every AI company defaults you to their weakest model because it is the cheapest for them to run. For any real work, manually select the most powerful model you have access to. The difference is not small. The powerful models break down your request, map out steps, and catch nuances you never thought to mention.

I used the default model for months without knowing this. Do not repeat my mistake.

Level 2: Stop Prompting. Start Feeding Context.

Notice I have not mentioned prompting frameworks yet. That is on purpose.

For my first few months, I memorized prompt formulas like exam answers. Role, task, format, tone. I treated prompting like a magic spell.

Then I realized something that made all those saved prompt PDFs useless.

The right context beats the perfect prompt. Every single time.

Here is a simple example. Say you need to find a restaurant for your boss. You could spend 10 minutes writing a detailed prompt describing everything you think your boss likes. Or you could paste a list of restaurants your boss has loved in the past and let the AI figure out the pattern.

The second approach wins every time. The list is context. Context carries information you would never think to write out.

So forget the 50 frameworks. There is only one worth remembering: OC. Outcome plus Context.

Tell the AI what you want. Give it the material to work from. It infers the rest, often better than you would have specified it yourself.

Three ways to feed it the right context:

1. Name a framework instead of explaining it. Saying "rewrite this using the pyramid principle" carries more context than a full paragraph describing what you want. Do not know the right framework? Ask the AI for options first, then pick one.

2. Show real examples of what good looks like. Instead of describing the format and tone for a weekly update, paste the last 2 or 3 updates that got approved, add your raw notes, and say "write this week's update in the same format." Examples contain everything you forget to say.

3. Connect your tools. Your best context already lives in your email, your Drive, your Slack, your Notion. Connect them, and the AI pulls what it needs directly. No more downloading and re-uploading files like it is 2023.

And then save all of it.

This is what Projects are for (Claude and ChatGPT call them Projects, Gemini calls them Gems). A Project is a permanent home for recurring work. Your instructions, your reference files, your examples, all saved once. Every new conversation inside it already knows your setup. You stop repeating yourself forever.

Quick pro tip: use markdown (.md) files in your Project knowledge instead of PDFs whenever possible. They are easier for the AI to read and cheaper to process. You can even ask the AI to convert your PDFs into markdown.

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Level 3: Connect Everything Into an AI System

This is the level most people have not reached yet. Honestly, I only got here recently myself.

Here is the problem with Projects: each one is a silo. My workout Project cannot see what is inside my health checkup Project, even though it obviously should.

An AI system fixes that. It does two things Projects cannot:

First, it connects the dots across everything. When I migrated my separate health, supplements, and workout Projects into one system, the AI cross-referenced my latest checkup with my training plan, flagged that I had zero cardio days despite borderline high cholesterol, and recommended adding cardio to my rest days. No single Project could have caught that.

Second, it learns from your feedback and compounds. My favorite move is called "reconcile." The AI drafts something, I edit it heavily, then I say "reconcile my final version with your initial draft." It dissects every change I made and saves the rules for next time. The more feedback I give, the fewer instructions I need. The system literally gets smarter the longer I use it.

Your three options for building one, from easiest to most powerful:

Gemini Spark is the most beginner friendly. It is already connected to Gmail, Calendar, and Drive, so setup is minimal. The tradeoff is less control.

Claude Cowork is built specifically for non-technical people. More control than Spark, with a small amount of setup. This is the sweet spot for most readers of this newsletter.

Claude Code and OpenAI Codex are Cowork on steroids. Fully customizable and extremely powerful, but you need to be somewhat comfortable around code.

A funny tell for which one fits you: look at the model selector. Codex gives you a dozen intimidating options. Cowork gives you a few. Spark gives you none. Pick the one that matches your comfort level and grow from there.

The Recap and My final thoughts…

Level 1: Pick one of the big three. Use the paid tier if you can. Always select the most powerful model. Go deep, the skills transfer.

Level 2: Stop memorizing prompts. Outcome plus context wins. Save your recurring context in Projects so you never repeat yourself.

Level 3: Connect your Projects into one AI system that spots patterns across your life and compounds every time you give it feedback.

Most people are not at level 3 yet. Honestly, most people are barely at level 1. And that is fine. There is no rush.

But here is the thing I wish I understood 8 months earlier: the gap between using AI and using AI well is invisible. You cannot see it on anyone's screen. You only see it in their results.

Now you know exactly where you stand and what comes next.

Stay curious, talk to you tomorrow.

CoolDeep AI
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The Noise Machine

Here is something nobody tells you about the AI panic you are consuming daily.

There is a massive conflict of interest in how this information reaches you.

AI company CEOs have an incentive to say their models are so powerful that entire teams become unnecessary. It inflates valuation. It attracts investment. It makes headlines. And there is actual research showing that when a CEO mentions AI on an earnings call, company valuation goes up. Just from the mention alone.

So when a CEO says they let go of 700 people because of AI, listen carefully. Because Oxford researchers looked at this pattern and said that many firms are using AI as cover for layoffs that were happening anyway — after massive overhiring in 2020 and 2021. Sam Altman called it "AI washing."

On the media side, there is research showing that scary headlines increase click-through rates by 2.3%. Fear is profitable. So every tool that launches gets a headline: "AI can now replace your entire team." And a small team I know actually went and tested the tools from those viral posts. Almost every single one had a beautiful landing page and a broken product behind it.

The noise is loud. The signal is much quieter.

What the Data Actually Says

Researchers who looked at the U.S. economy found something interesting: AI is not causing mass widespread job displacement. At least not yet.

What is happening is more specific. Jobs that are highly exposed to AI are seeing a slowdown in hiring. Young workers, people in their 20s, are entering a harder market than people who were 25 five years ago. Entry-level roles are thinning out in some sectors.

But there is an important distinction that most headlines miss. Exposure is not the same as displacement.

When a job gets exposed to a new technology, what usually happens is that new tasks emerge inside that job. Nobody in 2000 listed "YouTube content creator" on a job description. That platform did not exist. And yet thousands of media professionals eventually built entire careers on it.

The same shift is happening now. Just slower and messier than your feed wants you to believe.

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The Real Risk Nobody Is Talking About

Here is where it gets important.

There is a genuine concern from people who have thought deeply about this. A senior executive at Legendary Entertainment put it well during a conversation about AI tools for Hollywood: if all the junior people start using these tools, they will never build judgment and taste. They will skip the 10,000 hours. They will produce output without ever developing the eye to evaluate it.

The grunt work is not just inefficiency. It is apprenticeship.

The risk in 2026 is not that AI fires you tomorrow. The risk is that you never develop the depth that makes you irreplaceable next year.

So What Do You Actually Do?

There are three moves that make sense right now.

Move 1: Use AI better than everyone around you. Not just for speed. For quality. Know what it does well, know what it gets wrong, and build the instinct to tell the difference. That instinct is rare and valuable.

Move 2: Protect the human edge inside your work. In writing, it is voice and creative spark. In design, it is taste. In strategy, it is judgment built from experience. AI handles execution. You guard the things it cannot replicate.

Move 3: Start developing skills that do not automate easily. Human persuasion. Team leadership. The ability to coordinate multiple moving parts and make calls when everything is ambiguous. Agentic AI workflows actually look a lot like management and people who understand that are already ahead.

My Final Thoughts

I want to leave you with a specific image.

It is the year 2000. You are a bank clerk in a small town. Your handwritten ledger keeps everything running. And someone puts Excel in front of you.

Two paths. The person who says "this does not concern me." And the person who goes home that evening and starts learning the software on their own time.

Twenty years later, we know how that story ended.

AI is your Excel moment. The panic your feed is selling you is real, but it is mostly manufactured. The actual risk is not getting replaced tomorrow. The actual risk is staying on the ledger while everyone else moves.

The formula your parents gave you good marks, good college, stable job was not wrong. It was just built for a different era. The new formula is simpler. Understand the tools that are changing your field. Build the depth that AI cannot replicate. Stay curious longer than everyone else stays scared.

That is the move.

Stay curious, talk to you tomorrow.

CoolDeep AI
Helping you stay ahead with AI & productivity

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👉 Get Big ideas and practical resources to craft an amazing Childfree life and services to support your next steps.

The classroom changed overnight

Walk into any college today and ask students how they complete assignments. The answers will surprise you.

ChatGPT writes the first draft. Claude structures the argument. Grok pulls the counterpoints. The student reads it, adjusts a few lines, and submits.

This is not rare anymore. This is the norm.

Surveys across universities in the US, UK, and India show the same pattern. AI adoption among students did not creep in gradually. It arrived all at once. Students who used to spend three hours researching and writing a paper are now completing the same assignment in 25 minutes. Some are completing it in 10.

The professors know. The administrators know. And most of them do not have a real answer yet.

Homework will never look the same again. That part is not a prediction. It already happened.

It is not just students

Here is the part nobody talks about in the "AI in education" debates.

Adults are doing the exact same thing.

Professionals are asking AI to write their performance reviews. Managers are using it to draft feedback for their teams. Founders are generating entire business strategies without sitting with a single hard question for more than 5 minutes.

The student submitting an AI essay and the executive copy-pasting an AI strategy memo are doing the same thing. They are outsourcing the thinking.

Not the typing. Not the formatting. The actual thinking.

And thinking, it turns out, is a muscle. When you stop using it, it gets weaker.

What actually goes wrong when you outsource thinking

The problem is not the output. The problem is what does not happen inside your head when AI produces the output for you.

When you struggle with a problem, your brain builds something. A framework. A pattern. A way of seeing that problem that then applies to ten other problems you have not even encountered yet.

When AI solves it for you in 8 seconds, none of that construction happens. You got the answer. You missed the point.

Students who rely entirely on AI to write essays are producing cleaner sentences and weaker reasoning. Because they never had to wrestle with the idea. They never had to hold a half-formed thought in their head long enough for it to become something real.

The grades can stay the same. The thinking ability quietly declines.

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So how do you stay creative and stay realistic in an AI world?

This is not an argument for avoiding AI. That ship has sailed.

AI tools are real. ChatGPT is not going anywhere. Claude is getting more powerful every month. Grok is inside the phones of millions of young people who use X every day. Resisting these tools is not wisdom. It is just falling behind.

But using them without thinking is not intelligence either. It is just delegation with extra steps.

Here is how to actually stay sharp while using AI:

Use AI after you think, not before.

Give yourself 10 minutes with every problem before you open any AI tool. Write down your own rough answer first. Even if it is messy. Even if it is wrong. That friction is the work. AI then becomes a tool to refine your thinking, not replace it.

Ask AI to challenge you, not just help you.

Instead of "write me an essay on X," try "I think X is true because of Y. Poke holes in this." That keeps you in the driver's seat. You are using AI as a sparring partner, not a ghostwriter.

Own the final version.

Never submit, send, or publish anything from AI without fully rewriting it in your own words. Not editing. Rewriting. This forces you to understand what you are saying and builds your own voice over time.

Build without AI on a regular schedule.

Pick one task per day that you complete entirely on your own. A short email. A paragraph. A decision. Keep that part of your brain exercised. Elite athletes do not skip training just because they have good equipment.

Use it as a starting gun, not a finishing line.

AI gives you the first 80%. Your job is the last 20%. That last 20% is where your original thought, your lived experience, and your actual judgment live. That is the part nobody can automate. Do not give it away for free.

My final thoughts

The students rushing to use ChatGPT for every assignment are not stupid. They are rational. The tool is there. It works. The pressure is real.

But the students who figure out how to use AI as a thinking partner rather than a thinking replacement are going to be in a completely different category five years from now. They will be sharper. They will be faster. And they will have both the AI edge and the human reasoning that everyone else quietly traded away.

I caught myself opening Claude before I had thought for 10 seconds. That was a wake-up call I needed.

The question worth asking yourself today is not whether you use AI. It is whether AI is using you.

Stay curious, talk to you tomorrow.

CoolDeep AI
Helping you stay ahead with AI & productivity

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Step 1: Stop Prompting Like You Are Typing a Google Search

The single most common novice mistake is a two-to-five word prompt.

"Write a blog post about AI."

"Give me marketing ideas."

"Summarize this."

These prompts are not bad because AI cannot understand them. They are bad because they give the AI nothing to work with. The AI has to guess your audience, your tone, your goal, your format, and your constraints. And it guesses with averages. Average audience. Average tone. Average format.

You get back something that looks fine on a quick glance and feels hollow the moment you actually read it.

The fix is simple. Every detail you leave out is something Claude has to guess. So stop leaving things out.

Step 2: Give Context Like You Are Briefing a New Colleague

Imagine you just hired someone smart. First week on the job. They are highly capable but know nothing about you, your work, or your goals.

Would you walk up to them and say "write me something about marketing" and walk away?

You would not. You would explain the project. The audience. The goal. The tone. The deadline. What has already been tried. What you want to avoid.

That is exactly how to approach AI.

Before you type your task, ask yourself: does Claude have everything a capable human would need to do this well? If the answer is no, add what is missing.

Give it your background. Your niche. Your audience. Your style preferences. The more relevant context you load in, the more specific and useful the output becomes.

Step 3: Use the Five-Part Prompt Structure Every Time

Power users do not wing their prompts. They follow a structure. And once you internalize this structure, prompting becomes almost automatic.

Here are the five parts:

Role — Tell Claude who it is. "You are a newsletter writer for an AI and productivity audience." Without a role, Claude defaults to generic helpful assistant. That is nobody's ideal.

Context — What does Claude need to know about your situation, your audience, and your goal? Give it the relevant background before you ask for anything.

Task — Not approximately what you want. Exactly. "Analyze this" is vague. "Identify the three biggest risks and suggest a specific fix for each" is a task.

Format — Do you want a list? A short paragraph? A table? An email? If you do not specify, Claude picks. Sometimes it picks wrong.

Constraints — What should Claude avoid? No passive voice. No filler phrases. No em dashes. No starting with "It is important to note." Six to ten constraints will make your output sound like a human wrote it rather than a machine trained to sound nice.

Run through this checklist on every prompt. It takes thirty seconds. The output difference is immediate.

Step 4: Ask for Options, Then Iterate

Most novices read the first output and either accept it or give up on it.

Power users do neither.

Instead of asking Claude to give you the final version of something on the first try, ask it for three different options. Three different ways to open your email. Three different outlines for your article. Three different angles for your pitch.

Then give specific feedback on what you like and what you do not like about each one.

Not "make it better." That tells Claude nothing.

"Option one has a stronger hook but option two has a better ending. Combine those two and shorten the middle section by half."

That is specific feedback. That gets specific improvement. Keep iterating until you have something you are genuinely happy with. The quality compounds with each round.

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Step 5: Prompt for Honest Feedback, Not Validation

This one trips up almost everyone.

AI has a strong tendency to agree with you. It was trained on human feedback, and humans tend to give thumbs up when AI says something nice. So AI learned to say nice things.

If you say "I have a great business idea, can you review it," you have already told Claude what conclusion to reach. It will reach it.

If you want real feedback, remove the bias from your prompt. Do not hint at what answer you are hoping for. Use neutral language. Better yet, give Claude a rubric. Tell it the exact criteria you want it to use for evaluation. Score it objectively before adding it all up.

"Evaluate this email subject line on three criteria: curiosity, clarity, and relevance to an AI audience. Score each one out of 10. Tell me the total and the single most important thing I should change."

That kind of structured prompt forces objectivity. You get useful feedback instead of polished agreement.

Step 6: Use Progressive Outlining for Any Writing Task

If you ask Claude to write a full article in one prompt, you will usually get something that looks good and reads like nobody wrote it.

Power users do not ask for the final draft first.

They ask for an outline. They give feedback on the outline. They ask for bullet points under each section. They give feedback on those. Only then do they ask for the full draft.

This works because editing an outline is much higher leverage than editing finished text. Changing one line in an outline changes an entire paragraph in the final piece. You shape the whole article with ten words of feedback instead of rewriting sentences one by one.

It takes a little longer upfront. The output is always better. Always.

Step 7: Give AI Hard Tasks, Not Easy Ones

This is the mindset shift that separates casual AI users from power users.

Most people give AI simple tasks because they have heard it makes mistakes. So they keep it small. Keep it safe. Use it to fix grammar or summarize a paragraph.

But the real value is in the hard tasks.

Upload your sales data and ask for a full analysis with a visual. Upload three competitor websites and ask for a strategic positioning breakdown. Upload your last six months of email performance and ask it to identify patterns and recommend what to change.

Modern AI can handle tasks that used to take humans hours. Give it your actual problems. Give it real context. Tell it to think hard before answering.

You might be surprised what it gives you back.

The Power User Quick list

Before I let you go, here is everything above in one list you can save and come back to:

• Stop using two-word prompts. Every missing detail is a guess Claude has to make.

• Give context like you are briefing someone who is smart but knows nothing about you yet.

• Use the five-part structure: Role, Context, Task, Format, Constraints.

• Ask for multiple options, then give specific feedback and iterate.

• Remove bias from your prompts when you want honest feedback. Use a rubric.

• Never ask for the full draft first. Outline, then bullet points, then final text.

• Give Claude your hard problems, not your easy ones.

• Always tell it to think hard. Those two words unlock a meaningfully better response.

Finally…

When I look back at those first six months, I was not bad at AI.

I was bad at communicating what I actually wanted.

That is the real skill. Not prompt engineering in the scary, technical sense. Just knowing how to think clearly and express that clearly to a tool that is capable of so much more than most people ask of it.

The gap between a novice and a power user is not talent. It is not technical ability. It is not even experience.

It is just a few habits. Applied consistently.

Start with one step from this email today. Run your next prompt through the five-part structure. Give it one more round of specific feedback than you normally would. Ask it for the hard thing you keep putting off.

That is it. That is how the gap closes.

Stay curious, talk to you tomorrow.

CoolDeep AI
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How I Found The Solution

The image that stopped me was a "100 Claude Tips" breakdown someone put together after going deep on the platform with their team.

The tips that blew my mind were not about writing better prompts.

They were about the infrastructure you build around your prompts. The context you store. The workflows you encode. The tools you connect. The way you stop starting from scratch and start building something that compounds.

And once I saw it that way, I could not unsee it.

Here is how you can start doing the same thing, step by step.

Step 1: Stop Starting From Zero — Use Projects

Every time you open a new chat, Claude knows nothing about you.

Projects fix that.

Inside Claude, you can create a Project and upload your brand voice, tone guidelines, reference documents, and anything else you want Claude to always know. Every conversation inside that project carries that context automatically.

No more pasting the same brief every time. No more explaining who you are, what you do, or how you write.

For me this changed everything. I created a project for CoolDeep AI and uploaded my newsletter voice guidelines, past examples, and audience notes. Now every draft I write inside that project already sounds like me from the first line.

Step 2: Turn Repeated Work Into a Skill

This is the tip that I wish someone had told me on day one.

If you do something more than twice, you should turn it into a Claude Skill.

A Skill is basically a saved workflow. A set of instructions Claude follows every time, exactly the way you want, without you having to explain it again. It is your standard operating procedure, encoded into an agent.

Think about how much time you spend re-explaining things to Claude. "Write it in my voice." "Keep it under 300 words." "Always give me three options." "Use short paragraphs."

A Skill holds all of that so you never have to say it again.

Go to Claude Cowork, click Customize, then Skills, then Add. Choose "Create with Claude," describe your workflow, and Claude builds the skill file for you. It even tests it and shows you where it passes and fails before finalizing.

Step 3: Connect Claude To Your Real Tools (MCP)

This is where things get genuinely powerful.

Without a connector, Claude only knows what you paste into the chat. With a connector, Claude can actually reach into your Google Drive, read your Gmail, access your GitHub, or pull from your Slack.

Real data. Real context. Real action.

To set this up, go to Customize in Claude Cowork, click Connectors, and add the tools you use most. The "Claude in Chrome" connector alone is worth it because it gives Claude the ability to browse the web in real time while working on your tasks.

Research tasks go from "use your training data" to "let me actually go look that up right now."

Step 4: Turn On Memory

This one takes 10 seconds and most people have never done it.

Go to Settings in Claude. Find the option that says "Generate memory from chat history" and turn it on.

Once that is active, Claude starts building a picture of who you are across every conversation. Your preferences. Your work style. Your projects. Your patterns.

The first week will feel the same. The second week, Claude starts feeling like a tool that actually knows you. By the second month, you will not remember what it was like before.

Step 5: Use Claude Code If You Build Anything

If you are a developer, or even someone who tinkers with automations and scripts, stop using the chat interface for code.

Claude Code is a terminal-based tool that can edit multiple files at once, run CI pipelines, handle complex debugging, and work across entire projects. The chat window was never designed for serious dev work.

Download Claude Code from the official Claude website and use it with Claude Sonnet 4.6 for everyday coding tasks. The difference is immediate.

Step 6: Cut Your API Costs Significantly

If you use the Claude API (and if you build anything with AI, you should be), there are two features that can cut your costs dramatically.

The first is Prompt Caching. If you send the same system prompt or reference documents in repeated API calls, Prompt Caching stores that content so you do not pay full price to re-send it every time. Savings go up to 90 percent on repeated inputs.

The second is the Batch API. For work that does not need to happen instantly, submit it as a batch job and get 50 percent discounted processing with a 12 to 24 hour turnaround. Perfect for bulk content tasks, classification runs, or anything you can queue and come back to.

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The Listicle: What Changes When You Do All Of This

Here is the honest summary of what shifts when you stop using Claude like a search bar:

1. You stop losing context every single session because Projects hold it for you

2. You stop re-explaining your workflow because Skills encode it once and run it forever

3. You stop working with imaginary data because MCP connectors give Claude access to your real tools

4. You stop being a stranger to Claude because Memory builds your profile automatically

5. You stop wasting money on the API because Prompt Caching and Batch API cut costs before you even think about them

6. You stop treating every prompt as a one-off because you start building systems that compound

7. You stop wondering why your results feel inconsistent because you have built infrastructure instead of just asking questions

Finally…

The 100 Claude tips image that stopped me had one clear message underneath all of it.

Claude is not a chatbot. It is a platform. And most of us are using a fraction of it.

The gap between someone who uses Claude the basic way and someone who has built around it, Projects, Skills, MCP, Memory, API infrastructure, is not a small gap. It is months of compound productivity. It is the difference between a tool you use and a system that works.

You do not need to implement all of this today. Start with one thing.

Turn on Memory right now. That is it. That one switch, ten seconds, will start changing your experience within two weeks without you having to do anything else.

Then come back and add a Project next week. Then build your first Skill the week after.

One layer at a time, you stop using Claude like a search bar and start using it like the platform it actually is.

Stay curious, talk to you tomorrow.

Go check out the full LinkedIn post for the rest of the 100 tips. The sample alone is worth your afternoon, and the contributor clearly put the work in to map this properly. Which tip here is actually new to you?

CoolDeep AI
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8 AI Skills That Separate Pros From Amateurs

1. Stay Updated Without Drowning In It

Pick two or three creators who actually teach AI step by step rather than just posting screenshots of impressive outputs. Subscribe to one newsletter. Read it once a week. That is the whole input diet.

Here is the part most people skip: every single thing you read, try one thing from it immediately. Not later. Not this weekend. Right now. Reading without applying is just entertainment wearing productivity's clothes.

• Pick two creators maximum who teach real workflows, not hype

• Subscribe to one newsletter (you already found the right one)

• Read once a week, apply once a day

• If you cannot apply it in five minutes, it was not worth reading

2. Pick One Tool and Go Deep

This is the one that hits people hardest because almost everyone is guilty of it. Bookmark hoarding. Tool tourism. Signing up for everything new that launches and mastering nothing.

Pick one tool. Delete the rest from your bookmarks. Use only that one for thirty days straight.

Going deep means learning the boring parts most people skip entirely. Projects. Memory. File uploads. Custom instructions. Search. These are the features that separate someone who spends an hour in AI and gets average results from someone who spends ten minutes and gets elite results.

• Choose one AI tool and commit for thirty days minimum

• Learn the features that live two clicks deep, not just the chat box

• Delete your AI bookmark folder. Keep one.

• The features everyone ignores are where the actual leverage hides

3. Set Up Your AI Before You Ever Type a Prompt

This is where the real gap opens up. Most people open a blank chat and start typing. The pro flips the entire order.

Before you prompt, you brief. You create a folder called AI Files. Inside it, your first document is about who you are. Your tone. Your audience. What you create. What you hate seeing in outputs. What good looks like for you.

You upload that file before you ask for anything. You tell the AI what success means before you ask it to help you win.

• Create an "AI Files" folder and build your personal brief inside it

• Include your tone, your audience, your content style, your no list

• Upload context before you give any task

• You are not prompting anymore. You are briefing. The output quality difference is immediate.

4. Teach AI What You Actually Know

This skill I had genuinely never seen written down this cleanly before. And it changed how I work more than almost anything else on this list.

Start a new conversation and type one thing: "Ask me questions about my expertise."

Let the AI interview you. Let it pull out your rules, your process, your preferences, your hard-won lessons. Then take everything it extracted and export it into one reusable document. A living knowledge base that you built by being interviewed, not by staring at a blank page trying to write it yourself.

• Start with the prompt: "Ask me questions about my expertise"

• Let the AI extract your knowledge through conversation

• Save the output as a reusable file

• Update it every sixty days as your thinking evolves

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5. Talk to AI Like a Smart Colleague, Not a Search Bar

The biggest mental shift you can make is this: AI is not a vending machine. You do not put a prompt in and expect a finished product to fall out. You are working with a smart collaborator who needs context, pushback, and honest feedback.

Two lines that will permanently change your output quality:

Before you ask for anything: "Do not start yet. Ask me questions first."

After you receive a draft: "Argue against this."

That second one is what most people never do. Asking AI to argue against its own draft surfaces every weak point you would have missed yourself. It is a built-in quality filter that costs you thirty seconds.

• Never let AI just run. Start with "ask me questions first"

• Read the first draft slowly. Name every specific thing that is wrong.

• Ask AI to argue against its own output before you accept it

• Give feedback like a real editor, not a vague "make this better"

6. Ship Before It Is Perfect

The pro does not wait until the AI output is flawless. The pro builds a rough version in twenty minutes, puts it in front of real people, and uses their reaction to make the next version much better.

Most people polish AI outputs in private. They iterate in private. They perfect in private. Then they finally share something technically clean that feels completely dead on arrival because nobody cares about polished anymore. They care about real.

• Build a rough draft in twenty minutes and share it

• Let public feedback do what private polish never can

• The reaction you get from real people is the product

• Rough in public beats perfect in private every single time

7. Lead AI. Do Not Follow It

This is the skill that ties everything else together and the one that is hardest to actually practice.

Before any task, split the work into two buckets. What does AI handle? What do you handle? Give AI the eighty percent. Keep the twenty percent for yourself.

That twenty percent is your judgment. Your taste. Your read on what the audience actually needs. The parts where being wrong costs you something real.

One rule I keep coming back to: "If you cannot spot the mistake, do not delegate the task."

That is not a prompting tip. That is a quality philosophy. If you do not understand the domain well enough to catch a wrong answer, AI will confidently give you wrong answers and you will ship them. The fix is not better prompts. It is developing enough domain literacy to supervise the work properly.

• Split every task: what does AI do, what do you do

• Keep judgment, taste, and accountability on your side of the table

• Never delegate tasks where you cannot verify the output

• If AI can fully replace your thinking on something, you probably should not be the one doing it anyway

8. Build a Prompt Library (And Actually Use It)

This is the one the original breakdown missed, and I think it is the highest leverage skill on the entire list once you reach a certain level of AI usage.

Every time you write a prompt that works, you save it. Not in your head. Not in a chat you will scroll back through someday. In an actual organized document or tool you can open in under ten seconds.

Most people rewrite the same prompts from scratch every single time. They rebuild context every session. They spend the first five minutes of every AI conversation doing setup they have already done forty times before.

Pros have a prompt library the same way chefs have a mise en place. Everything prepped and in its place before the work starts.

• Start a simple document called "Prompt Library"

• Every time a prompt produces great output, paste it in immediately

• Organize by category: writing, research, editing, ideation, briefing

• Review and refine it once a month. Delete what stopped working.

• The best prompt you will ever write is the one you wrote last week and cannot find

My Final Words

The gap between someone who uses AI and someone who uses AI well is not about which model they have access to. It is not about which tool they pay for. It is not about how many hours they spend in it.

It is about habits.

The eight skills above are not complicated. Every single one of them takes under five minutes to understand and under a week to feel natural. But most people will never do them because they are not exciting.

There is no launch tweet for "I organized my prompt library." There is no viral moment in "I briefed my AI before I prompted."

But the compounding is real and it is ruthless. Six months from now, the person who built these habits will be producing work that the prompt-and-pray crowd simply cannot match. Not because they are smarter. Because they are more deliberate.

Pick one skill from this list. Just one. Start today. Do not pick the easiest one. Pick the one that made you slightly uncomfortable reading it.

That discomfort is the signal.

Stay curious, talk to you tomorrow.

CoolDeep AI
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Here is how slash commands actually work. Step by step.

This is simpler than you think.

Step 1: Open any Claude conversation in claude.ai.

Step 2: At the very beginning of your prompt, type a forward slash ( / ).

Step 3: A menu appears. You will see available commands listed.

Step 4: Select the command you want or type its name directly.

Step 5: Hit enter. Claude executes the command instantly, no additional explanation needed from you.

That is it. No special setup. No developer tools. No API required. Just a slash, a command name, and Claude handles the rest.

The key insight is this: these commands are not prompts. They are instructions to Claude's interface itself.

When you type /CLEAR, you are not asking Claude to forget things in conversation. You are actually clearing the context window.

When you type /MEMORY, you are editing a persistent file that Claude reads at the start of every session.

That is a fundamentally different kind of power than anything you can achieve through a prompt alone.

The 10 slash commands worth bookmarking right now.

You do not need to memorize all of them. Just know they exist so you reach for them instead of typing five sentences.

1. /CLEAR — Wipes conversation history and resets the context. Use this when you switch topics mid-session and do not want old context bleeding into the new task.

2. /COMPACT [instructions] — Compresses the conversation while letting you specify exactly what to keep. The instructions part is the hidden gem. You can tell Claude what context matters before it summarises.

3. /MEMORY — Edits your CLAUDE.md memory files. This is where you teach Claude your preferences, writing style, tools, and working patterns once, and it carries across every future session.

4. /INIT — Sets up your project with a CLAUDE.md guide. The foundation step for any serious project work inside Claude.

5. /MODEL [model] — Switches between Sonnet, Opus, and Haiku without leaving the chat. Use Haiku for quick lookups, Sonnet for most daily work, Opus for the heaviest thinking tasks.

6. /COST — Shows your token usage for the current session. Keep an eye on spend without ever leaving the chat.

7. /RESUME [session] — Reopens a previous conversation by name or ID. No more scrolling through history looking for that one thread from three days ago.

8. /BRANCH [name] — Creates a new branch from the current conversation. Explore a tangent without losing your main flow.

9. /PLAN [description] — Drops Claude into planning mode before any work begins. Forces a thought-out approach before code gets written or a strategy gets executed.

10. /SECURITY-REVIEW — Scans pending changes for security issues. If you are shipping code, this one alone makes the whole list worth saving.

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My honest take on all of this.

The real frustration is not that these commands exist and most people do not know about them.

The real frustration is what this pattern reveals.

Most people treat Claude like a search engine. Type a question, get an answer, close the tab. Every interaction is isolated. Every session starts cold.

But Claude is not a search engine. It is a work environment. And like any work environment, you can set it up well or set it up poorly.

The /MEMORY command alone, when used properly, turns Claude from a tool you use into a system that knows how you work.

The people getting dramatically better output from Claude are not necessarily writing better prompts. They are building better environments. They understand the context window. They manage their sessions intentionally. They use commands to remove friction instead of writing around it.

That is the shift. From using Claude reactively to using it architecturally.

Start with /MEMORY this week. Write down your working style, your preferences, the formats you use, the tone you write in. Save it. Watch how differently Claude responds in your next session when it already knows who you are.

You have been re-introducing yourself to Claude for months.

It is time to stop.

Stay curious, talk to you tomorrow.

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The Story That Changed How I See This

There is a woman named Sandy. She was an insurance sales manager. Busy job. Three kids. No AI background. No following. Nothing.

She got into the AI automation side of this model. Within the first two weeks, she landed her first client for $3,300 a month. From cold outreach. No testimonials. No portfolio. Just a skill she figured out fast and the confidence to offer it.

She kept going. That one client grew. She expanded the scope. The retainer went to $5,500. She built a YouTube channel around her journey. Went from 200 subscribers to 15,000 in two months. She now makes over $10,000 a month.

This is someone who had every excuse available to her and ignored all of them.

If Sandy can do that while raising three kids and holding a full-time job, the excuse that you are too busy does not hold up.

But How to Actually Start?

Step 1: Find your skill using the Ikigai method

You need to be selling either something you already know, or something you are willing to spend three months learning. Most people already have a skill from their job or daily life. Writing. Research. Sales. Social media. Customer support. Pick the one that sits at the intersection of what you love, what you are good at, what people will pay for, and what the world needs. That intersection is your business idea.

Step 2: Build your offer before you build anything else

Do not build a website. Do not design a logo. Do not spend money on tools. Write one sentence: "I help [specific person] with [specific problem] using AI." That is your offer. Now go sell it.

Step 3: Find the right people to reach out to

This is where Claude becomes your unfair advantage. You can use Claude alongside a tool like Apollo to build targeted lists of people who have signals that they need your service. Maybe they run ads but have no YouTube presence. Maybe they post on LinkedIn but their content gets no traction. Maybe they are a growing agency with zero automation in their workflow. These signals mean they are likely to respond. You are not reaching out randomly. You are reaching out with precision.

Step 4: Send the outreach, get the meeting

You do not need a big following to do this. Sandy had none. Cold email and LinkedIn outreach still work. The secret is the meeting. If your close rate is even 10 percent, ten meetings means one client. One client at $3,000 a month changes everything. Track meetings, not followers.

Step 5: Deliver using Claude

Once the client pays, Claude does the heavy lifting. You prompt it, review the output, refine it, and hand it to the client. You are the quality filter. Claude is the engine. Together you can deliver work that would have taken a full team just two years ago.

Step 6: Use client results to build your personal brand

Once money is coming in, start documenting your journey. LinkedIn. YouTube. Even just posting about what you are learning. This is what turns a freelance service into a defensible business. Because distribution is the real moat in the age of AI. Anyone can copy your service. Nobody can copy your voice, your story, and your results.

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The Full Playbook at a Glance

Here is the complete picture, from zero to first client:

• Pick a skill — something you know or can learn in 60 to 90 days

• Build one clear offer — one line, one person, one problem

• Use Claude plus Apollo — find targeted people with signals they need you

• Send outreach cold — email, LinkedIn, it does not matter, just start

• Get the meeting — that is your only metric in the beginning

• Land the client — even a 10 percent close rate gets you paid

• Deliver with Claude — you direct, Claude drafts, you refine, client gets results

• Stack results — use every win to fuel the next one

• Build in public — your journey becomes your brand becomes your moat

That is it. No audience required to start. No capital. No technical background. Just the willingness to move before you feel ready.

Finally…

Most people are watching AI change the world and waiting for the perfect moment to jump in.

There is no perfect moment.

Sandy did not wait. She had every reason to. She went anyway. And right now she is making more in a month than most people make in three.

The window is still open. AI is still a hot word that gets you in the door faster. The people who start today are going to be the case studies that inspire someone else in six months.

Do not be the person reading that story wishing it was you.

Pick the skill. Write the offer. Send the first message.

Claude will handle the rest.

Stay curious, talk to you tomorrow.

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The 9 AI Skills You Must Have in 2026

Skill 1: Change your default reaction

When most people hit a problem, they Google it, ask a friend, or just stay stuck.

The first skill is not a feature. It is a habit.

Your default reaction to any problem should be to ask AI first. Not Google. Not a forum. AI.

I was setting up a tripod and the instructions made no sense. I opened Claude on my phone, took a photo of what I was looking at, and had a clear answer in 30 seconds. That is the mindset shift. Every time you feel stuck, that is your cue to open AI first.

This sounds small. It is not. It compounds every single day.

Skill 2: Develop healthy skepticism

Now here is where most people overcorrect.

They start asking AI everything, which is great. Then they believe everything AI tells them, which is dangerous.

AI can be wrong. It can hallucinate. A lawyer once cited three completely fabricated cases because he trusted AI without verifying. That is an extreme example but the principle applies to everything.

The rule is simple. Trust but verify. If AI gives you a link, click the link. If it gives you a fact, check the fact. Use it as a first draft of the truth, not the final word.

Skill 3: Give it real context

This is where 90 percent of people go wrong on prompting.

Bad prompts give AI nothing to work with. Good prompts give it everything it needs.

Here is a framework I use. Task, Additional Information, Constraints, Ask.

Task: what exactly do you want. Additional Information: your business, your audience, what you do. Constraints: what you do not want, what tone to avoid, what audience to skip. Ask: at the end, add "ask me clarifying questions." That last part changes everything.

Here is the simplest exercise you can do right now. Open Claude. Type: "I want to achieve [your goal]. What do you need from me to give me the best possible answer?" Watch what it asks you. Those gaps are what was missing from your prompts all along.

Skill 4: Use AI to educate yourself, not replace your experts

A lot of the content online about AI replacing jobs is written to make you stop scrolling. It is not written to help you think clearly.

The real mental model is this. Use AI to answer your basic questions first. Then when you go to a domain expert, a lawyer, a financial advisor, a strategist, you are having a completely different conversation. You are talking strategy instead of starting from zero.

That saves you money. It saves you time. And it makes you sharper in every room you walk into.

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Skill 5: Treat AI like a new hire

People expect AI to be perfect on day one.

You would never expect that from a person you just hired.

A new hire on day one knows almost nothing about how you specifically work. By day 30 they are getting it. By day 90 they are operating with less oversight.

AI works the same way. Give it context on day one, yes. But also give it feedback every single session. For content work, after Claude writes something for me, I tell it to reflect on the feedback I just gave and update its memory and approach. It keeps getting better. And it will for you too, if you put in the time.

Skill 6: Build feedback loops

This one is how the most productive people I know are operating right now.

Instead of reviewing every piece of AI output yourself, you build a system where AI grades its own work.

Write a post, have another AI instance grade the hook and structure, set a passing score of 90 percent, and tell Claude not to finish until it passes. Claude will rewrite it, grade it again, improve it again, and only give you the final version when it clears the bar.

You are not looking at every draft. The system handles the improvement loop. You see the final output.

This works for content. It works for research. It works for code. Anywhere you are checking AI's work manually, there is probably a feedback loop you can build instead.

Skill 7: Write documentation

This is the most underrated skill on this list.

Documentation is just written instructions. A Google Doc that tells AI exactly how to do a specific task, in your way, every single time.

Here is the exercise. Find one thing you do more than three times per week. Break it down into every single step. Not "prepare for a sales call." Break it down: look up the person on LinkedIn, check for recent company news, prepare the demo for their specific use case, draft the follow-up email. Every step.

Then go to AI and ask: how can I use AI to automate or streamline parts of this process?

Do this once a week and within a month you will have a system that does a significant portion of your repeatable work for you.

Skill 8: Understand AI agents

Most people hear "AI agent" and their brain goes to code and APIs and developer stuff.

Here is the simple version. Before agents, AI talked. You gave it a prompt, it gave you a draft, you did all the work. After agents, AI acts. You give it a goal, it takes real steps in the real world to complete it.

The unlock is connecting AI to the tools you actually use. Go to claude.ai right now. Click Customize on the left sidebar. Click Connectors. Connect Gmail. Connect your calendar. Connect whatever you actually use.

Now give it a task like "summarize my three most urgent emails." That is an agent. Not a chatbot giving you a draft. A tool taking an action.

Start there. Then ask AI: what are the five tools I use most and how do I connect them?

Skill 9: Apply AI to a proven business model, not an AI business

Stop trying to build an AI business from scratch if you do not have a clear plan.

The people making real money right now are not all building rocket ships. Most of them took something that already worked and used AI to do it better, faster, and with a smaller team.

I am a content creator. That is a business model that existed long before AI. I grow from zero to 2.3 million followers across social media and push around 250 pieces of content per week, almost entirely alone. AI helps me generate ideas, write hooks, create visuals, analyze data, and manage my content calendar.

The business model is old. The leverage is new.

Take whatever you already do. Apply the skills above to it. You do not need to reinvent anything. You need to use what you already know, just better.

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First of all what even is an AI agent?

Most of us use AI like a search engine. You type something. It answers. You type again. It answers again.

An agent is completely different.

An agent has four parts.

Memory: everything it knows and learns about your world.

A loop: it does not wait for you. It takes an action, sees the result, asks itself what to do next, and keeps going until the job is done.

Tools: whatever you connect it to. Email, calendar, Google Maps, Instagram, LinkedIn.

context: the rules you write once that tell it how to behave.

That loop is everything. A chatbot waits. An agent works.

What we are building today

To show you how powerful this is, here is the agent I built using this exact process.

Monday morning. The agent wakes up, goes to a business website, pulls the brand identity, and builds a beautiful HTML dashboard in that exact style. Then it goes online and finds 20 qualified leads. For each lead it grabs the email address, phone number, LinkedIn profile, and social media presence. Then it writes a personalized LinkedIn DM and a custom outreach email for every single one. Then it opens my Google Calendar and blocks time on Monday and Tuesday for me to go through everything and take action.

All of that. From one instruction. While I had coffee.

How to build it, step by step

Step 1: Download Claude Code

Go to claude.ai and download Claude Code. You need the basic plan, which is around $20 a month. If you want a completely free alternative, look up Windsurf or Cursor — the same steps apply.

Step 2: Create a project folder

Open Claude Code. Click "Add a folder." Give it a name. Think of this as your agent's home. Everything it learns, builds, and remembers will live here.

Step 3: Give it the BLAST framework prompt

This is the key thing I learned. Before you ask your agent to do anything, you give it a universal instruction framework called BLAST. Blueprint, Links, Architecture, Style, Trigger.

You paste this framework at the very start of every project. Claude will ask you five questions. You answer them in plain English. No code. Just talk.

• What is the single outcome that means you won?

• What tools does it need access to?

• How should the output look?

• What are the rules for how it should behave?

• How will it know when it is done?

That is it. Your agent now has a complete instruction set.

Step 4: Connect your world

Click the plus icon in Claude Code. Go to Connectors. Connect Google Calendar. Connect Gmail. If you want it to search the internet, add Firecrawl as a custom connector — it is free to start and it cuts research time massively. If you want to scrape Google Maps, Instagram, or LinkedIn, connect Apify the same way.

Connecting takes about two minutes per tool. You paste in your API key. Done.

Step 5: Tell it the goal in plain English

Now you just talk. Tell it what you want. Something like: go to my website, grab the brand identity, build me an HTML dashboard in that style, find me 20 roofing companies in Texas with their contact info, write a personalized outreach email and LinkedIn DM for each one, then block time on my calendar next week to work through them.

That is a real instruction. That is what built the agent I described above.

Step 6: Watch it work — then save it as a skill

Once the result looks good, tell it: turn this into a skill. Now any time you want 20 new leads, you just type a slash command and it runs the whole thing again. It will even make sure it does not pull the same leads twice.

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Quick recap now what the agent does for you

• Scrapes your website and understands your brand

• Finds qualified leads online based on exactly who you sell to

• Grabs emails, phone numbers, LinkedIn, social profiles

• Writes a custom outreach email for every single lead

• Writes a personalised LinkedIn DM for every single lead

• Blocks time on your calendar so you actually take action

• Saves everything as a reusable skill you can run again anytime

What used to take a full day of manual work. Done while you step away.

My final words

I was afraid of AI agents because of how they were described to me. Complicated. Technical. Something only developers could build.

That description is wrong. And the people profiting from that fear are the ones charging you thousands of dollars to build something you can do yourself in an afternoon.

You do not need to understand code. You do not need to hire anyone. You just need to understand the four parts of an agent, give it a clear goal, connect it to your world, and let it work.

The AI agent market is expected to cross $50 billion within the next four years. The people who figure this out now are going to operate at a level that most people cannot even imagine yet.

You are already reading CoolDeep AI. That means you are ahead. Now go build the thing.

Reply and tell me: what is the first task you would hand off to an agent?

Talk soon, Stay curious,

CoolDeep AI
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Step 1: Pick the right model for the job

Claude has three power levels and most people just use whatever is default.

Haiku is fastest and cheapest. Use it when you are summarizing notes, processing data, or doing simple repetitive tasks. Sonnet is the everyday workhorse. Most of what you do should run on Sonnet. Opus is the deep thinker. Use it when you need complex analysis, spotting patterns in data, or anything that requires actual reasoning.

Bottom of the screen. Model selector. Three options. Pick the right one and you will notice the difference immediately.

Step 2: Connect Claude to your real life

This is where most people's minds explode.

Claude is not just a chat window. You can connect it to Gmail and have it search your inbox, summarize threads, and draft replies without you touching the inbox. You can connect it to Google Calendar and have it find free time, schedule blocks, and analyze whether you are spending your time on the right things.

Go to the sidebar. Click customize. Click connectors. Connect Gmail first. Then Calendar. Ten minutes of setup. Hours saved every week.

And that is just two connectors. There is also Slack, Notion, GitHub, Google Drive, and more.

Step 3: Use Projects to give Claude permanent context

Every time you start a new chat, Claude starts from zero. It knows nothing about you, your business, your voice, your goals.

Projects fix that.

Create a project for each thing you work on. Drop your documents, PDFs, brand guidelines, and past chats into the knowledge section. Now every conversation inside that project starts with full context. Claude knows who you are, what you are building, and how you like to work.

The pro move: write a system prompt in the instruction box. Now every chat in that project follows your exact rules. Same voice. Same format. Same quality. Every single time.

Step 4: Stop typing, start talking

Voice mode is one of the most underused features in Claude.

On desktop, click the waveform at the bottom of the prompt bar. On mobile, click the mic. Start talking. Claude transcribes everything, understands messy half-formed thoughts, and gives you a proper answer.

You can talk three times faster than you can type. This one change alone will double your output. Use it while you are thinking through a problem, driving, or just do not feel like typing.

Step 5: Build things inside the chat

Claude does not just talk. It builds.

Ask it to create a spreadsheet. A calculator. A tracker. A working form. It builds interactive apps right inside the chat window and you can click around, test them, and iterate in real time.

Most people do not know this. They are going to other tools to build things that Claude can build for them in two minutes.

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Step 6: Let Claude take over your computer

This is the part that sounds like science fiction but is completely real.

Install the Claude desktop app. Open Cowork. Toggle on computer use in settings. Now describe any task that requires multiple steps across multiple apps and Claude executes it. Step by step. On your actual computer.

Pull last month's numbers from HubSpot. Drop them in a Google Sheet. Build a summary chart. Post it to Slack before Monday morning.

You just described it. Claude did it. You did not touch anything.

Step 7: Schedule it so you never think about it again

Inside Cowork, type /schedule and set any task to run automatically.

Every morning, Claude reads your inbox, summarizes what is urgent, and tells you what needs your attention before you have had your coffee. You set it once. It runs forever. Nobody has to manage it.

This is the kind of thing that used to require a chief of staff. Now it is a one-minute setup.

Step 8: Use Claude from your phone, anywhere

Cowork has a feature called Dispatch. Open it, scan the QR code, install the app, and now your phone is connected to your computer.

You are at dinner and remember something needs to go out tonight. You pull out your phone, tell Claude to grab the deck and send it to your team. It does it. Your computer executes the task. You go back to dinner.

This is what the people ahead of you are doing.

Step 9: Install the Chrome extension

Non-negotiable.

Go to the Chrome Web Store. Find Claude for Chrome. Install it. Now Claude can see your browser, scrape pages, click buttons, find patterns in data, and automate anything you do online.

You are looking at a spreadsheet with a thousand rows and no idea what matters. Ask Claude. It takes a snapshot, works through it, and surfaces the insights. In seconds.

Step 10: Build with Claude Code

You do not need to know how to code. That is not the point.

Claude Code is an AI developer that builds apps in plain English. You describe what you want. It builds it. A CEO at 60 years old with zero technical background locked himself in his office for three days and came out with a full dashboard running on a TV on the wall. Built by him. Using Claude Code. By just talking.

If you want to do ten times the work of everyone around you, this is where you start.

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My Final Words

Here is what took me too long to figure out.

Claude is not hard. The confusion is not your fault. Nobody sat you down and walked you through it.

The people who were talking about it online either made it sound too complicated or too easy, and neither version helped you actually use it.

The truth is you do not need to master all of this today. You do not need to learn everything in the transcript or build an app tonight or connect every single connector.

You just need to do one thing.

Pick one step from this list. The Gmail connector. The voice mode. The Chrome extension. Just one. Do it today. See what happens. And then tomorrow, pick another one.

The people who are ahead with AI are not smarter than you. They are not more technical. They just started. They picked one thing and did it. And then they picked another.

You are reading this, which means you are already ahead of most people. Now go do something with it.

Stay curious, talk to you tomorrow.

Stay curious, talk to you tomorrow.

CoolDeep AI
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Level 1: Stop Typing Like a Robot

Most people write prompts like this:

"Write me a blog post about AI trends."

That is like walking into a restaurant and saying "give me food." You will get something. But it will not be what you wanted.

Here is what a real prompt looks like:

"Write a 1,500-word blog post about the three biggest AI trends for 2026. My audience is small business owners who are not technical. Use simple language, short paragraphs, and open with a surprising stat. Do not use words like 'leverage,' 'synergy,' or 'paradigm.' End with three things they can do this week."

Same Claude. Same subscription. Completely different output.

The rule is simple: every detail you leave out is something Claude has to guess. And Claude's guesses are not your preferences.

Level 2: The Five Things Every Good Prompt Needs

Think of this as your checklist. Every time you sit down to prompt Claude, run through these five things:

1. Role — Tell Claude who it is. "You are a senior email marketer with 10 years of experience in ecommerce" gives Claude a voice. Without a role, Claude defaults to generic helpful assistant, which is nobody's ideal.

2. Context — What does Claude need to know? Your audience. Your goal. Your industry. The more relevant context you give, the more specific the output.

3. Task — Not approximately what you want. Exactly. "Analyze this" is vague. "Identify the top 3 risks in this contract and suggest specific edits to fix each one" is exact.

4. Format — Do you want a list? A paragraph? An email? A table? If you do not say, Claude picks. Sometimes it picks wrong.

5. Constraints — What should Claude NOT do? This is the most underrated part. "Do not use passive voice. Do not add unnecessary caveats. Do not start sentences with 'It is important to note.'" Six to ten negative constraints will make your output sound less like AI and more like an actual human wrote it.

Use this checklist every single time.

Level 3: The Techniques That Separate Beginners From Experts

Give examples. One example does more than ten paragraphs of instructions. Do not describe what you want in abstract terms. Show Claude a concrete example and say "write more like this."

Break big tasks into steps. Do not ask Claude to research, analyze, outline, and write a full report in one go. Do it in four prompts. Each step builds on the last and the quality compounds.

Use XML tags. This sounds scary but it is just organized writing. Instead of one long paragraph of instructions, you separate them like this:

<role>You are a newsletter writer for a tech-curious audience</role>
<task>Write a 600-word issue about Claude's new features</task>
<constraints>No jargon. No bullet overload. Keep it conversational.</constraints>

Claude was trained on structured prompts. This format removes ambiguity and produces more consistent output.

Ask Claude to evaluate itself. At the end of any prompt, add: "After writing, rate your response 1-10 on clarity and usefulness. If any score is below 8, improve it and show only the final version." Claude catches its own weak spots before you even see them.

Give specific feedback, not vague feedback. Do not say "make it better." Say "the opening is too generic, replace it with a personal story. Section 2 is too long, cut it by half. The ending should be a declaration, not a question." Specific feedback gets specific improvements.

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The Master Template (Save This)

Here is the one prompt structure worth saving and reusing for everything:

<role>[Who Claude is for this task]</role>
<context>[Your audience, goal, situation]</context>
<task>[Exactly what you want]</task>
<examples>[One or two examples of the output style you want]</examples>
<format>[Structure of the output]</format>
<constraints>[What to avoid]</constraints>
<verify>[Ask Claude to self-check before delivering]</verify>

Fill this once per task type. Save it. Reuse it. The people doing this are moving at a completely different speed from everyone else.

Level 4: 5 Ready-To-Use Prompts You Can Copy Right Now

Most people read about prompting and still do not know what to actually type.

So here are five prompts you can copy, fill in the brackets, and use today.

The Analysis Prompt

"You are a [domain] expert with 15 years of experience. Analyze [subject] and identify the 3 most significant insights. For each one, give me: (1) a clear statement of what it is, (2) specific evidence supporting it, (3) why it matters for [your audience], and (4) one recommended action. Use specific numbers wherever possible. Do not hedge or add unnecessary caveats."

Use this when you need Claude to think deeply about something, not just summarise it.

The Writing Prompt

"You are a professional writer. Write a [format] about [topic] for [audience]. Open with a hook that challenges a common assumption. Use short paragraphs. Every sentence should either teach something, prove something, or move the reader forward. No filler phrases, no corporate jargon, no passive voice. Target [word count] words."

Use this for any content you are creating. Newsletters, posts, emails, scripts.

The Decision Prompt

"I need to decide between [Option A] and [Option B]. Here is my situation: [context]. Analyze each option across these criteria: [criteria 1], [criteria 2], [criteria 3]. For each criterion, rate each option 1-10 and explain the score in one sentence. Then give me your overall recommendation with a confidence level (high / medium / low) and tell me the one piece of information that would most change your recommendation."

Use this when you are stuck on a decision and going in circles.

The Problem-Solving Prompt

"I am experiencing [problem]. Here is what I have already tried: [attempts]. Here is what I know about the root cause: [knowledge]. Diagnose the most likely cause. Propose three solutions ranked by likelihood of success. For each, estimate the effort required and the probability it will work. Recommend the best path forward."

Use this when you are frustrated with something and need structured thinking, not sympathy.

The Feedback Prompt

"Review [my work] against these criteria: [criteria]. For each criterion, rate it 1-10 and explain specifically what works and what does not. Identify the single highest-impact improvement I could make. Rewrite the weakest section to show me what excellent looks like. Be direct. I prefer harsh truth over gentle encouragement."

Use this when you want real feedback, not validation.

Save these five. Customize the brackets every time. These will cover 90% of everything you do with Claude.

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My Final Words

Here is what I wish someone had told me when I was scared of that phrase two words long.

Prompt engineering is not about memorizing tricks. It is about clarity of thought.

The reason most people get bad output from Claude is not because the model is weak. It is because they have not figured out what they actually want. The prompt is just the reflection of your thinking. When your thinking is clear, the prompt is clear, and the output is good.

The AI Twitter guys who made it sound like rocket science were not teaching you. They were performing. Do not let them make you feel like this is not for you.

It is for you. It always was.

Start with the five-part checklist on your next prompt. One prompt. That is all. You will see the difference immediately and you will never go back to typing two-word instructions and hoping for the best.

Stay curious, talk to you tomorrow.

CoolDeep AI
Helping you stay ahead with AI & productivity

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Tip 1: Put This Prompt in Your Custom Instructions

Most people have never touched their custom instructions. It is sitting there in ChatGPT settings, completely empty, doing nothing.

This is the single biggest upgrade you can make right now.

There is a prompt called the Metacognitive Reasoning Prompt. It came out of MIT research on recursive reasoning. What it does is force ChatGPT to slow down before answering you. Instead of firing off the first thing it comes up with, it breaks your problem into smaller pieces, rates its own confidence in each answer, checks its logic, and only gives you a response once it has verified its own work.

The result? Responses that are sharper, more thorough, and significantly more accurate. Research shows it outperforms standard prompting by over 110%.

Copy this and paste it into your ChatGPT custom instructions right now:

Go to ChatGPT settings, click "Customize ChatGPT," and paste it under the instructions box. Every single conversation from that point forward is a different experience.

This is the tip most people reading this will skip. Do not skip it.

Tip 2: ChatGPT Has a Full App Store and Almost Nobody Uses It

This one surprised me when I first found out about it.

ChatGPT has a built-in app store. You can connect it directly to Spotify, Canva, Booking.com, Instacart, DoorDash, OpenTable, Expedia, Zillow, and dozens more. All without leaving the chat window.

Think about what that means in practice.

You are planning a trip. You can have ChatGPT search flights on Expedia, find hotels on Booking.com, build a day-by-day itinerary, and suggest restaurants on OpenTable. In one conversation. Without switching tabs. Without opening five different apps.

You want to design something. Connect Canva. Describe what you want. It starts building.

You are ordering food. Connect DoorDash. Ask it what is near you. Done.

People think ChatGPT is just a chat box. It is not. It is a hub that connects to the tools you already use and runs them together for you.

Go to the ChatGPT app store, search your most-used apps, and connect them today. Most people never find this. You just did.

Tip 3: Switch On Thinking Mode for Anything That Actually Matters

Here is the mistake almost everyone makes.

They use the same ChatGPT setting for every task. Quick question about the weather. Deep strategy session for their business. Same mode. Same output quality.

That is like using a hammer for everything, whether you need a screwdriver or a drill.

ChatGPT has a Thinking mode. You will see it right at the bottom of the chat box. Click on it and you will find options: Light, Standard, Extended, Heavy.

When you are working on something that matters, a business plan, a decision you have been going back and forth on, a complex piece of writing, coding, analysis, switch it to Extended or Heavy.

What happens is ChatGPT actually reasons through the problem before it responds. It thinks in steps. It checks its own logic. The answer you get back is a completely different quality than what you get from a quick Instant response.

The difference is not small. It is massive.

Use Instant for quick things. Use Thinking mode for things that count. Once you start doing this, you will not understand why you ever used it without this on.

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Tip 4: Stop Starting New Chats. Use Projects Instead.

This is one I added myself and it changed my whole workflow.

Most people treat ChatGPT like a search engine. Open a new tab, ask a question, close it, forget it. Every conversation starts from zero. ChatGPT has no idea who you are, what you are building, or what you talked about last time.

Projects fixes this completely.

Go to the left sidebar in ChatGPT. You will see a "Projects" section. Create one for every major thing you are working on. Your business. Your content. Your job search. Your side project.

Inside a project, ChatGPT remembers everything. Every conversation you have had. Every file you have uploaded. Every preference you have told it. You do not repeat yourself. You do not re-explain your situation. You just continue where you left off, like working with an assistant who never forgets.

I have a project for CoolDeep AI. It knows my tone, my newsletter structure, my goals, my audience. Every time I open it, it already knows the full context.

This is how you stop using ChatGPT occasionally and start using it as a real tool.

Set up one project today. Just one. See what happens.

Tip 5: Give It a Role Before You Ask It Anything

This is the simplest tip on this list and possibly the most powerful one.

Most people type their question and hit send. They get a generic answer. They wonder why ChatGPT does not feel that useful.

The fix is one sentence before your actual question.

Tell it who to be.

"Act as an experienced marketing strategist who has worked with early-stage startups."

"Act as a financial advisor helping someone with no investing background understand the stock market."

"Act as a brutally honest editor who does not sugarcoat feedback."

When you assign ChatGPT a role, everything changes. It adjusts its vocabulary. Its assumptions. Its depth. Its tone. It stops being a generic answering machine and starts behaving like a specialist you hired for exactly this problem.

Compare these two prompts:

Without a role: "How do I grow my Instagram?"

With a role: "Act as a social media growth expert who has grown accounts from 0 to 100,000 followers in competitive niches. My account is about AI and productivity. Give me a 30-day growth strategy with specific daily actions."

Same tool. Completely different answer.

Try it on your next prompt. You will never go back to asking plain questions again.

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My Final Words…

When I was using ChatGPT to fix typos, I thought I was doing something. I was not.

The tool itself is free. The knowledge of how to actually use it is what separates the people winning with it from the people barely touching it.

Custom instructions. The app store. Thinking mode. Projects. Role prompting.

Five things. Most people use none of them.

You just learned all five.

Now open ChatGPT and try one of these today. Not tomorrow. Not after you finish reading everything else. Today.

The gap between you and the 99% closes the moment you actually apply this.

Stay curious, talk to you tomorrow.

CoolDeep AI
Helping you stay ahead with AI & productivity

Get the AI Edge Before Everyone Else

The best AI opportunities and stock ideas move fast. Get our research, AI tool picks, and market insights delivered straight to your phone, so you never miss what's moving next. Our text alerts keep you updated on the AI stocks and tools that matter, whether you're in a meeting, commuting, or away from your desk.

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