You’ve been picking projects that aren’t yours.

I lead multiple programs developing AI models at Google. Twenty years in tech. The same trap has caught me, every cycle.

Below are the three exercises I actually run when there are too many AI ideas on the table and nothing on it is finished.

The trap.

You watched a tutorial yesterday. Stripe dashboard held to the camera. Thirty thousand a month. AI agent built in two weeks.

You took notes. You bookmarked the tutorial. You opened a doc.

You started something.

You stopped.

It’s not the tutorials. The tutorials are fine.

The problem is copying them.

The project in that tutorial was shaped by someone else’s drive, someone else’s customer, and someone else’s timing. When you copy it, you’re trying to graft someone else’s life onto yours.

When the work gets hard, the energy runs out. Because it wasn’t yours to begin with.

That’s why your folder fills up with half-started projects and finishes nothing. Not because you lack discipline. Because the decision to start happened before you ever did the work of deciding what was actually yours to build.

The three exercises below are what fix that.

They come from people who have spent decades thinking about how humans choose what to do with their lives. They aren’t a sequence you run end-to-end. They’re three different lenses on the same question.

Use one. Use all three. Whichever lands first.

Exercise 1: Yearning Octopus.

From a Tim Urban article called How to Pick a Career That Actually Fits You.

Urban’s idea: everyone has a yearning octopus inside their head. Five tentacles. Each wants something different. They don’t get along.

For someone trying to build with AI, the five tentacles look like five drives.

• Personal. Making something that means something to you.

• Social. Respect from peers.

• Lifestyle. Freedom from a day job.

• Moral. Helping people, having an impact.

• Practical. Making money, paying the bills.

Different drives want different builds.

The respect drive picks an app, because peers see apps and apps are status. The lifestyle drive picks something that runs without you, because the goal is freedom, not more hours. The moral drive picks a problem you can’t ignore. The practical drive picks a service, because services pay this month.

When the drive and the project don’t match, the work stalls around week three. The project isn’t bad. The drive behind it just isn’t yours.

This is why “just pick an idea and start” advice fails. The drive doing the picking has to be the drive that finishes. If you let the wrong one pick, you start, then quit.

Run it.

Step 1. Pick an AI project you’ve thought about. Maybe one you almost started.

Step 2. Ask which of the five drives is actually pulling you toward it. Not the one that sounds best out loud. The one that did the actual pulling.

Step 3. If nothing comes to mind, ask why you haven’t started. “I’d look stupid” is social. “I’d lose money” is practical. “It wouldn’t matter to anyone” is moral. The fear points at the drive too.

That’s your top drive. The honest one. The one you wouldn’t say to a stranger at a dinner party.

Then ask Urban’s question: is this actually mine, or did society hand it to me?

If the answer is “society handed it to me,” you’ve found the cleanest reason most projects stall.

Exercise 2: 5/25 Rule.

Attributed to Warren Buffett. Doesn’t matter if he said it.

It works.

You’ve considered more AI projects than you remember today. Twenty-five, easy. Maybe more. They’re in sticky notes, in voice memos, in dead Notion docs, in half-renamed folders.

The 5/25 Rule cuts the noise.

Run it.

Step 1. Write down 25 things you’ve considered building with AI. Force the number. Pull from every dead doc, every voice memo, every napkin.

Step 2. Pick the 5 most important to you. Circle them.

Step 3. Cross out the other 20.

The part most people miss.

Crossed out doesn’t mean backlog. It means off the table. Buffett’s framing: they get no attention until the 5 are done.

This is the move that actually changes something in your head.

Your brain has been cycling 20 silent ideas in the background. Every time you sit down to work on one, the others pull at your attention. That’s the tax you’ve been paying.

Killing the 20 stops the cycling. The 5 start getting the focus the whole list was eating.

It feels uncomfortable. That’s the point. If it feels easy, you didn’t bury them.

Your top 5 only matters when the other 20 are off the table.

Exercise 3: Napkin Test.

Customer development thinking, distilled.

If you can fit your project on a napkin and you know one specific person to give it to, that’s the project.

You now have 5 candidates from Exercise 2. They all feed the drive from Exercise 1. They all came from your own list.

But only one of them is the project you actually start.

To find it, you run each through two filters.

Filter 1: The napkin.

Can you describe what this project does in one sentence?

Not a paragraph. Not three sentences. One. Short enough to fit on a napkin.

If you can’t, you don’t understand the project well enough yet. That’s not a flaw in the project. It’s a signal that the project is still vague in your head, and vague projects don’t finish.

Filter 2: The name.

Can you name one specific person who would actually use this?

Not “small business owners.” Not “indie hackers.” A specific person. By name. Someone you could text right now and they’d recognize the problem.

If you can’t name the person, you don’t have a customer. You have an audience in your imagination. Audiences don’t pay. People do.

Scoring.

Pass both filters: that’s the project you start. Fail either: back to the dead list. Two candidates pass both: you have a luxury problem, pick by gut.

The reason this filter is so cruel is also why it works. Vagueness hides on a list of 25. It hides on a list of 5. It does not survive one sentence and one name.

One sentence. One name. That’s the project.

A worked example.

Say you have 25 ideas that range from “AI tutor for my niece” to “an automation that summarizes legal contracts.”

Exercise 1. You run the yearning check. Your top drive is lifestyle. You don’t want another job, you want freedom from the one you have.

That kills half the list. The agency-style services are out. The “10k MRR SaaS” is out. They’re more work, not less.

Exercise 2. From the 25, you circle 5 that fit lifestyle. Cross out the other 20.

You now have 5 candidates. All five fit your drive.

Exercise 3. You napkin-test all 5.

The legal contract summarizer fails Filter 2. You don’t know any lawyers.

The niece tutor passes both, but it doesn’t feed the lifestyle drive on its own.

The “morning briefing for solo founders” passes both. You can describe it in one sentence. You can name three specific solo founders who’d use it.

That’s the project.

Notice what just happened. You went from 25 vague ideas to one specific project with a real first customer, in three exercises. No tutorial required.

How you know.

Run each candidate through the three exercises before you start anything.

A drive that’s actually yours. Five candidates pulled from your own list. One project you can fit on a napkin and hand to someone real.

That’s how you know what to build with AI.

Not someone else’s thumbnail. Not someone else’s vision. Not the project that pays the loudest creator on YouTube.

The project that survives all three exercises is the one that finishes.

What’s next.

The full walkthrough is in this video, with examples and the exact prompts I use:

Watch here

Next week: how to build the smallest possible version of the survivor project in a weekend. No coding. No buying another course.

If this helped, send it to one person who keeps starting AI projects they don’t finish. That’s how Growsembly grows and how these stay free.

— Guney

Growsembly is a weekly newsletter for non-technical creators and professionals who want to actually finish what they start with AI. Subscribe here.

For months, editing one issue of this newsletter took me two hours.

Now it takes about twenty-five minutes.

The fix was not a better prompt or a faster typing speed. The fix was opening the right tool.

Most people are using one Claude. There are three.

If you open Claude in your browser and ask it questions, you are using one Claude.

There are three.

Claude Chat. Claude Cowork. Claude Code.

Each one is built for a different kind of work, and the one you reach for makes more difference than the prompt you write.

What each one is actually for

Claude Chat

This is the one you already know. You open claude.ai, type a question, and get an answer. It works in your browser, on your phone, and in the desktop app, and the conversation syncs across all three.

Chat is for thinking out loud once. A new idea you want to test. A single email you need to draft. A topic you want to understand quickly before a meeting.

When you close the window, the work is gone. That is the point.

Claude Cowork

This is the one most people have not heard of. It only lives in the Claude desktop app, and it is the one that changed how I run my week.

Cowork can see the actual files on your computer. It can open them, edit them, save new ones, and run a task you set on a schedule. Instead of you copying text in and pasting answers out, Cowork works on the files directly.

It also remembers your preferences across sessions, so the second time you ask it to do something, you do not have to re-explain who you are or how you want it done.

Claude Code

This one is for building real things. Web apps. Automations. Integrations. The kind of work that needed a software engineer eighteen months ago and now does not.

You can run Code in your terminal or inside the desktop app. Either way, it is built around how developers work, and if you have ever thought “I would build this if I knew how,” that is the room you have been missing.

All three run the same Claude underneath. They are not different intelligences. They are different capabilities sitting on top of the same model.

How the newsletter editing went from two hours to twenty-five minutes

I write Growsembly every week. For months, I was running drafts through Chat because Cowork did not exist yet.

The workflow was awful. I would copy a paragraph into Chat, ask for the edit, paste the result back into my document, and then catch the things Chat had silently changed that I did not want changed. Eight or nine passes per issue, twenty minutes a pass.

That is two hours of pure shuffle work per issue. The chat usage was so heavy that it forced me onto the Max plan.

When Cowork shipped, I rebuilt the editing process inside it.

Cowork edits the file directly, so the entire copy-paste loop disappeared. I read what changed, keep what I want, push back on what I do not.

Same writing work, about twenty-five minutes per issue. I dropped back to the Pro plan the following month.

The two-question test for picking the right one

You do not need to memorize anything. You need two questions, asked in order, and you stop at the first one that lands you on a tool.

Question one: does the work need to live in a file you will keep using?

If yes, that is Cowork. If no, that is Chat.

Question two: does it need to run on its own when you are not there?

If yes, that is Code. If no, Cowork still works.

Two questions, three tools, and no more guessing about which window to open.

A small experiment if you want to feel the difference

Download the Claude desktop app if you do not have it. Pick a task you actually do every week. Something boring is best.

Ask Chat to do it. Then ask Cowork. Then ask Code.

Pay attention to what clarifying questions each one asks you and what approach each one takes. They will arrive at similar answers, but the way they get there is the part that tells you which one belongs in your week.

What I am taking away

The tool you reach for first becomes the tool you reach for always. That habit calcifies inside a couple of weeks, and after that you stop noticing what it costs you.

I lost about ninety minutes per newsletter for half a year before I noticed.

If you are running the same task in Chat for the fourth time this month, the question is not how to write a better prompt. The question is whether you are in the right window.

See you next time.

— Guney

Two weeks ago, a friend texted me.

He’d been reading about AI businesses for months. Watching the YouTube creators. Lurking in Discord. Buying the courses. He wanted to know where to start.

I wrote back two words.

Sell a service.

He told me that wasn’t what anyone else was saying.

Everyone else was telling him to build an app.

So let me explain why I’m not.

The lottery you don’t have time for

For every AI app that makes a hundred dollars, there are roughly ten thousand attempts that never make a dollar.

Even if you can engineer, the build is barely half the work. The other half is making something people will pay for. Marketing it. Finding customers. Supporting them. Fixing what breaks.

That is lottery odds.

And the lottery takes months of your evenings before you find out if you drew a winning ticket. If you already have a real life in motion (a day job, a family, bills that depend on income actually showing up), you do not have that runway to burn.

So you flip the equation.

The service play

A service flips the risk.

Build an app:   You spend → you ship → you pray.
Sell a service: They pay  → you build → you ship.

Someone pays you first. You deliver after. You are selling a promise, and you build the specific deliverable with their money.

And the buyer doesn’t care if AI is doing the work. They care about the outcome.

Nobody asks a lawyer which software they used to draft the contract. They ask if it protects them.

The service business runs on exactly that logic.

Three people, no app, up to $6K a month

I work with three people who built this kind of business on the side of their day jobs in under ninety days.

Maya was a senior PM at a SaaS company. She writes competitive intelligence reports for startup founders. Twenty-five hundred per report. Five thousand a month by week eight.

David did eight years in management consulting. He writes investment memos on nights and weekends. Three thousand per memo. Six thousand a month by week twelve.

Priya did twelve years in B2B marketing. She runs a content strategy retainer service now. Thirty-five hundred a month by month three.

None of them built an app. None of them learned to code.

They sold a service.

They let Claude do the work.

The four-step system

I call it The Build System. It’s how you turn expertise into a service business without giving up your day job.

1. What to sell.       → A service, not a product.
2. How to find an idea. → Where your old expertise meets AI compression.
3. How to deliver.      → Build a Claude Skill once. Reuse it forever.
4. How to sign clients. → Ten real conversations with the right ten people.

Plus a 30-day plan you can start this weekend.

That is the playbook.

The part where most people stall is step 2.

The part everyone freezes on

Two questions:

1. What have you been paid to do at a senior level for more than three years?

2. Where does AI now make that work at least ten times faster?

The overlap between those two answers is your service.

That overlap is what I look for when I work with someone one-on-one. It is also what took me the longest to systematize across different industries, different career levels, different constraints.

So I compressed it into a Claude Skill.

It is called the Second Income Map.

You load it into Claude. You answer seven questions about your professional history. It produces a one-page service brief in about fifteen minutes:

• Your specific service direction

• Your target customer

• Your price band, anchored to pre-AI market rates

• A five-conversation validation test you can run this weekend

• The single next action

I am giving it away free.

Download the Second Income Map skill here.

Install it in Claude. Run it once. See what overlap your career hands you.

If the answer feels obvious in retrospect, that is the point.

— Guney

P.S. If a friend or coworker has been asking you the same question my friend asked me, forward them this email. The Map is free.

Prompt engineering is dead.

I know how that sounds. For two years it was the skill everyone was teaching, selling, and putting on resumes. I am telling you it is over, and I am going to show you the two practices that replaced it.

I have been in technology for twenty years. I currently lead multiple programs developing AI models at Google. The way I work …

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Three weeks ago, Anthropic shipped Claude Design.

You describe what you want. It builds the prototype, the pitch deck, the landing page, the mockup. Designers with ten-year portfolios just found out the job they spent a decade building is now a twenty-dollar subscription.

(Anthropic knocked seven percent off Figma’s stock in a single day when this launche…

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Your feed is about to be flooded with Opus 4.7 feature recaps. Skip them.

The feature recap is not the update. The update is a small set of habit changes, and if you miss them, your prompts still work. They just get quietly worse over time, and you will not be able to tell why.

This is the most common pattern I see when a new model ships. People read the …

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There is a specific kind of frustration that millions of people are experiencing right now with AI, and almost none of them can name what is actually causing it.

They open ChatGPT. They ask it to do something reasonable. Schedule a meeting. Pull live data from a spreadsheet. Monitor a competitor’s pricing page. Run a workflow while they sleep. The tool d…

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There is a question that has been quietly reshaping the education economy for the last several years, and most people who monetize their expertise have not stopped long enough to actually sit with it.

If anyone can learn almost anything for free, what are people actually paying for?

This is not a philosophical exercise. It is the operating reality of 2026. Large language models like ChatGPT, Claude, and Gemini can teach you more than most online courses. They can give you customized advice for your specific situation. They can answer your follow-up questions instantly. YouTube has become the largest free university in human history, with world-class tutorials on virtually every subject you can name.

The cost of accessing information has collapsed to near zero. And yet people are still spending money on education. In many cases, more money than before.

The thing they are paying for is not what most people think it is. Understanding this distinction is what separates the experts who build real income from the ones who keep launching products no one finishes.

Here is the uncomfortable truth about the online course industry.

Most people never finish the courses they buy. The data on this is not ambiguous. Self-paced online courses have completion rates that hover between 3 and 15 percent across virtually every major study conducted in the last decade. MIT published research showing that their MOOCs had a completion rate of just over 3 percent between 2017 and 2018. Udemy, one of the largest course platforms in the world, reports an 8 percent completion rate from their best-performing instructors. Harvard and MIT’s joint research found that more than half of registrants never even opened the first lecture.

These numbers are not anomalies. They are the structural reality of self-paced digital education. And they have consequences that go far beyond the buyer’s experience.

When your students do not finish your course, they do not get results. When they do not get results, they do not recommend you to anyone. When they do not recommend you, your next launch depends entirely on your ability to find new cold audiences. When you are perpetually hunting for new buyers instead of being carried by word of mouth from people who actually succeeded, your business is on a treadmill. You are running harder to stay in the same place.

The course model was built for an era when access to information was itself the value proposition. That era is over. The value proposition has migrated somewhere else entirely, and most people have not followed it.

What people actually pay for now is not knowledge. It is the environment that makes them execute the knowledge.

This is a distinction that sounds subtle but changes everything about how you design and sell an educational product. The problem your customer has in 2026 is almost never that they lack information. Their problem is that they have too much information and no structure to act on any of it. They have 47 browser tabs open. They have saved three courses they never started. They have a notes app full of ideas they have not touched in months. They know what to do. They do not do it.

The solution to that problem is not more content. It is structured accountability delivered in a live, time-bound, group environment.

That is what a cohort-based course is. And it is, I believe, the most underutilized and highest-performing format available to anyone who wants to turn expertise into income right now.

A cohort is a live, time-bound group program where a set of students go through material together on a fixed schedule. As opposed to a self-paced course where people log in whenever and work alone, a cohort creates structural forces that drive completion without relying on the buyer’s willpower.

When students are on a shared timeline, they cannot fall behind silently. When there is a live session on Tuesday, they show up on Tuesday or they watch the recording knowing everyone else has already moved ahead. When there is a community channel, they see peers posting progress, which creates social pressure to keep pace. When homework has a deadline, it gets done.

None of those forces exist in a self-paced course. In a self-paced course, the only accountability mechanism is the buyer’s discipline. And discipline, left to its own devices, is not a system. It is a wish.

The data reflects this. Programs with cohort structures, live support, and community see completion rates between 70 and 96 percent. Harvard’s altMBA, a four-week cohort teaching soft skills traditionally covered in a two-year MBA program, reports a 96 percent completion rate. Esme Learning’s cohort programs report 98 to 100 percent. When Harvard transitioned its case-method courses to incorporate peer collaboration, completion climbed to 85 percent while most of their MOOCs remained in the single digits.

The difference between 5 percent completion and 90 percent completion is not content quality. It is the format itself. The structure is doing the work.

This model is not new. That is one of the most important things to understand about it.

Every university in the world runs on cohorts. Every military training program. Every professional certification worth its weight. Every bootcamp that actually produces people who can do the job on day one. Harvard Executive Education charges $15,000 for a six-week cohort. The format has been the backbone of structured education for over a century because it works at a level that self-paced learning simply does not reach.

What changed is not the model. What changed is who can run one.

Until recently, you needed institutional backing, physical infrastructure, and administrative support staff to operate a cohort. Now you need a laptop, a Zoom account, and an audience of any size. The barrier to entry collapsed while the format’s effectiveness remained exactly where it has always been. That gap between low barrier and high performance is where the opportunity sits right now, and almost no one in the creator and expert economy is taking it seriously.

On Maven alone, the largest dedicated platform for cohort-based courses, over 12 instructors have crossed a million dollars in revenue and over 100 have crossed $100,000. Ship 30 for 30, a writing cohort that helps people publish 30 pieces in 30 days, has done over $10 million in lifetime revenue on a single, focused outcome. Building a Second Brain by Tiago Forte, a cohort that teaches people to organize their digital notes and research, has generated between five and ten million dollars. Ali Abdaal’s Part-Time YouTuber Academy has cleared $5 million helping people launch a YouTube channel and publish their first video.

Each of these programs delivers one specific outcome over a short, defined timeline. That narrowness is not a limitation. It is the design principle that makes them work.

If you are sitting on expertise worth monetizing, whether from a career, a craft, a transformation you have been through, or a skill people regularly ask you about, the cohort format gives you a structural advantage that no other model offers right now. Here are four principles that separate a well-built cohort from a live course that just happens to have a start date.

The first principle is transformation over education.

A cohort is not a course with a schedule attached to it. A cohort exists to help a specific group of people achieve one tangible result in a short period of time. The emphasis is on the word “achieve.” You are not selling information transfer. You are selling outcome delivery.

That outcome should be simple enough to state in one sentence and achievable within four to six weeks. “Publish 30 pieces of online writing in 30 days.” “Launch your YouTube channel and publish your first video.” “Build your first income system and make your first sale in 30 days.” Each of those is a clear, verifiable transformation. If your outcome description requires a paragraph of explanation, it is too complex. Narrow it down until a stranger can understand what they will have accomplished by the end.

The second principle is what I call Short, Narrow, Small.

Short means four to ten hours of live content delivered across two to four weeks. Narrow means you solve one problem and deliver one outcome. Small means you include only two to four core features: live sessions, a handful of resources, homework assignments, and a community space. That is it.

The instinct most people have is to add more. More modules, more bonuses, more content, more weeks. That instinct will destroy your cohort. The single greatest reason people abandon educational products is information overload. People feel good when they complete something. Your cohort’s entire job is to be completable. If you feel the need for more sessions or a longer timeline, you are teaching too much. Make it smaller.

The third principle is systems over curriculum.

Here is the truth that most educators resist: people do not want to learn. They do not care about your cohort, your framework, or your teaching style. They care about the result. Your job is to make the path to that result feel as close to done-for-you as possible, even though it is not a done-for-you service.

The way you do this is by building shortcuts into every step. Templates that are 80 percent complete so students only fill in the remaining 20 percent. AI prompts that generate first drafts they can edit rather than stare at blank pages. Checklists that eliminate decision fatigue. Examples pulled from real results so students can model their work on something proven rather than creating from scratch.

The best cohorts do not just teach. They hand people a machine that does most of the heavy lifting for them. That is what makes the difference between a student who understands the material and a student who actually executes it.

The fourth principle is sell before you build.

You do not need a completed curriculum to launch a cohort. You need an outline, an orientation video, and a clear description of the outcome. Sell the first cohort on that basis. Build the detailed slides and session content after you have confirmed there is demand.

This is one of the most powerful features of the cohort model: it has a built-in pre-sale mechanism. Because sessions are live and scheduled in the future, people must buy before the program begins. You validate demand before you invest the time to build. If nobody joins the waitlist, the concept or value proposition needs work. If people sign up, you build with confidence knowing real humans are waiting for what you are creating.

I spent four months designing my program before I launched the first cohort. I pressure-tested every component against twenty years of experience building and running programs at Google, Deloitte, and across government, healthcare, and enterprise technology. You do not need four months. But you do need to understand that a cohort is not something you throw together over a weekend. It is a structured system designed to produce a specific outcome. Treat it that way and the results will follow.

There is a flywheel embedded in this model that most people do not see until they experience it.

When your students complete the program, they get results. When they get results, they tell other people. When other people hear about it from someone they trust, your next cohort sells faster with less effort. When each cohort sells faster, you can raise the price because the product has a track record. When the price rises alongside demand, you have a real business, not a launch treadmill.

Compare that to the traditional course model. You spend months creating content. You launch it. Five percent of buyers finish it. Almost none of them get the result. No one recommends it. Your next launch requires the same cold outreach, the same ad spend, the same exhausting promotion cycle. The format itself is working against you.

A cohort reverses that dynamic entirely. Better outcomes lead to organic demand. Organic demand leads to sustainable pricing. Sustainable pricing leads to a business you can actually run without burning yourself out every quarter.

The market conditions supporting this shift are not going to reverse.

AI has made information functionally free. YouTube has made instruction functionally free. What remains scarce is structure, accountability, human interaction, and the kind of guided environment that makes people actually do the work they have been putting off. That scarcity is real, it is growing, and it is exactly what a cohort provides.

The people who recognize this early are building the next generation of education businesses while everyone else is still trying to sell pre-recorded content into a market that has moved on.

I have run two cohorts of my own program so far, and our successful candidates make their first sale within 30 days. I am not sharing theory. I am describing what I do on nights and weekends while still working full-time leading AI programs at Google. The model works because the format itself drives the outcomes. Not motivation, not content quality alone, but the structural mechanics of shared timelines, live interaction, and peer accountability doing what willpower never could.

If you have been sitting on expertise you know is valuable, if you have considered building a course or an info product but something about it has never felt right, if you have watched the market shift and wondered where the real opportunity is heading next, this is the direction it is moving.

I put together a free blueprint that walks through the complete system for building a cohort-based course from scratch, including the structure, the launch timeline, the marketing sequence, and the templates I use in my own program. You can get it at guneytopcu.com/cohortblueprint.

The window on this is open right now. The format is proven, the tools are accessible, and the market is ready. The question is whether you move on it while the space is still uncrowded or whether you wait until everyone else has figured out what you are reading right now.

Until next Monday,

Guney

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