I haven’t posted here since April 20. The last four months went into shipping Bookpay, our booking and payments platform, building a prototype for Hardy, and getting a team of interns up to speed. Good to be back!

I’ve been following the Meta trial this week. Twenty nine state attorneys general, a whistleblower testifying that the culture Zuckerberg built made it “practically impossible” to ship safety features, internal documents showing the company knew exactly what it was building. The number people keep repeating, $1.4 trillion, is almost too large to mean anything. But the story underneath it is small enough to sit with.

For a long time we read “move fast and break things” as a statement about speed. Ship before you’re ready. Iterate in public. Don’t let perfect be the enemy of good. It’s the kind of line founders quote approvingly all the time, usually without thinking much about what it’s actually excusing.

Watching this trial unfold, the phrase looks backwards now. It was never really about speed. It was cover.

Here’s what I mean. When you’re moving fast, you get to defer the hard question. Is this good for the people using it? You get to say: we don’t know yet, we’re still learning, the data isn’t in. Speed becomes the alibi for not asking, and not asking becomes the business model. The Meta whistleblower’s testimony shows this pretty clearly, that safety wasn’t rejected, it just was never seriously considered in the first place. Not because nobody thought of it, but because thinking of it too hard would have slowed the machine down.

That’s the trap. Not malice exactly, though this trial alleges plenty of that too. Something quieter and more available to any founder: the tech is neutral, we’re just building what people want, if they didn’t want it they wouldn’t use it. It’s a clean story, and it holds up right up until someone puts the internal memos next to the public statements.

It’s the same pattern tobacco companies ran in the mid 90s. Internal research pointing one way, public statements pointing the other, for decades, until the documents finally surfaced. The harm was clearer and more direct there. But the mechanism is the same: knowledge inside the company moves fast, accountability moves slow, and the gap between the two is where a lot of damage gets done quietly.

This isn’t just a Meta problem, either. YouTube paid $170 million over the same child privacy law in 2019. Epic Games paid $275 million in 2022. TikTok agreed to pay $400 million just this week, for the same underlying violation, collecting data on kids without consent. The number keeps climbing, and the fine is never really the point. What the government actually wants is the leverage a settlement buys, TikTok has reportedly changed its ownership, its privacy practices, its controls for young users, since it got sued. The money is just the mechanism that forces the company to sit still long enough to change something.

None of this is about scale. A company doesn’t need Meta’s size for the instinct to show up. Every product decision at Inkjin, what we track, what we nudge artists or clients toward, how a feature is designed to keep someone in the app a little longer, has a version of the same question. Is this built because it serves the person on the other end, or because it serves a number that’s being measured, with the two getting treated as if they’re the same thing.

They’re usually not the same thing. They just feel like it when growth is going well. A retention prompt that looks helpful can just be tuned to extend sessions. A recommendation that claims to surface better work can quietly favor whatever keeps someone scrolling.

The moment usually looks small from the inside. A founder is looking at a dashboard, a feature is testing well, the numbers are up, and somewhere in the room someone asks a quieter question, does this actually serve the person using it, or does it just serve the number on the screen. The easy move is to treat the numbers as the answer. The metric went up, so the feature must be good, and the question gets waved off as something to revisit later, once there’s more data, once things settle down. Later rarely comes. The feature ships, the number keeps climbing, and the question that got waved off quietly becomes the company’s actual position on the matter, without anyone ever deciding it on purpose.

The pattern shows up again and again once you start looking for it. Uber built Greyball, a tool that identified and showed a fake version of the app to regulators investigating whether Uber was operating legally in their city, a deliberate choice to keep growth going in places trying to shut it down. DoorDash quietly used customer tips to cover part of what it paid workers, rather than adding tips on top of a base rate, a mechanic that made pay look higher than what the company was actually contributing, until reporting in 2019 forced a change. Airbnb had internal and academic research showing hosts with Black-sounding names were booked significantly less often, years before the company built real guardrails against it. In every case, someone inside the company already knew the answer to the hard question. The company shipped anyway, and let speed stand in for an answer nobody wanted to give out loud.

What’s striking about this case is that the states aren’t just asking for money. They want Meta to remove like counts, kill autoplay, end disappearing Stories, stop multiple accounts, rework the recommendation algorithm. In other words, take apart the exact mechanics an entire industry got built on top of. If any of that lands, even narrowly, it’s not just Meta that feels it. Influencer marketing runs on those same signals, visible likes as a trust marker for brands, autoplay as free discovery, Stories as the format for “authentic” behind-the-scenes content. Growth marketers and ad agencies have years of playbooks tuned to how the current algorithm ranks and surfaces content, a rework makes a lot of that obsolete overnight. The ad tech tools that score creator performance or predict what goes viral using likes and watch time would need new models. Teen-facing brands, fashion, beauty, gaming, that built their whole reach strategy around Stories and Reels would need new channels. And beyond Meta itself, a ruling like this becomes precedent, other platforms with the same mechanics would start quietly auditing their own products before someone points at them next. Pull those threads out and you don’t just weaken Meta’s product, you weaken the infrastructure a lot of other businesses quietly built their whole model on top of, without ever asking who was really deciding the rules.

I don’t think there’s a clean rule here, something like “always choose the user” sounds right and means nothing in practice. But I think the useful move is smaller and more honest: notice when you’re using speed, or scale, or “that’s just how the algorithm works” as a reason not to look closely at what you built. That’s usually the moment to stop and look closer.

Meta will spend six to eight weeks in a courtroom finding out what happens when a company never stops long enough to look. Most of us will never face a jury for it. That doesn’t mean the question goes away. It just means nobody’s forcing us to answer it.

If the full internal picture behind a decision came out tomorrow, would the design still hold up, or would it need a story about deferred learning and eventual iteration to make sense? If it needs that story, speed is doing more work than it should.

I got my first job at fifteen to buy a pair of Converse All Stars. The ones Larry Bird and Dr. J wore. My parents wouldn’t buy them, so I worked for them. I still remember the feeling of putting them on.

I wanted to make money. Onassis was the poster on my wall. I wanted everything fast. Move fast, think faster, win. I was competitive then. I still am.

The hunger that starts you is almost never the hunger that keeps you. That took me a long time to understand.

I was sitting in my office when I got a call.

It was 2011. Someone I hadn’t spoken to in years, from a company I'd closed the book on long ago, asking if I wanted to buy back something I’d walked away from a decade earlier. He explained. I listened. I said I’d think about it.

For a day or two I slept on it. When I was younger, I would have said yes immediately. Something in me would have called it vindication. The Converse kid still wanting to win back what had been taken.

But I wasn’t that person anymore. That chapter had been closed for almost a decade. I’d started another company and brought in someone to manage it while I spent a few years at Google, then JWT, learning how real companies worked from the inside instead of trying to be the whole of something small. Somewhere in those years the hunger had quietly changed shape. I didn’t notice until the phone rang and the old answer didn’t come.

I said no.

Most people who know me were surprised. I think sometimes people see me on the surface and don’t go deeper. They assume the obvious move is the one I’d make. It almost never is.

I’ve been thinking about this for a long time. Not because I regret it. I don’t. But because it taught me something about founder stories I never read.

The thing I learned is this:

Making the thing, owning the thing, and keeping the thing are different things.

You can solve one and fail at the other two. Most people only ever solve one. And underneath all of them is a fourth problem. Figuring out which hunger you’re actually feeding, because it’s almost never the one you think.

The founder stories we hear collapse all of this into a single clean arc. That’s why they feel inspiring and, quietly, untrue. Once you’ve lived through even one of the three, you can’t read those stories the same way again.

Here are three I keep coming back to.

Story 1: The dishwasher who got fired for asking for rubber gloves

Most people know the ending of Michael Blake’s story. He wrote the novel that became Dances with Wolves. Kevin Costner made it into a film. The film won Best Picture, Best Director, and Best Adapted Screenplay at the 1991 Oscars. Blake walked onto the stage in a tuxedo and collected the award for a book thirty publishers had rejected.

That’s the poster.

Here’s the part nobody tells.

By 1987, Blake had already given up. He’d spent years in Los Angeles writing scripts nobody wanted. He’d slept in his car. He’d crashed on couches, including Costner’s, for almost two months, reading bedtime stories to Costner’s three-year-old daughter and writing the novel late at night.

Then he left. Drove east. Ended up in Bisbee, Arizona, a small mining town near the Mexican border. He got a job washing dishes at a Chinese restaurant for minimum wage.

The novel came out in 1988. It barely moved. When he asked his publisher about a second printing, they told him to write something else.

He kept washing dishes.

And then the detail almost nobody knows:

Blake got fired from the dishwashing job. For asking for a pair of rubber gloves.

That same week, Kevin Costner called him and asked him to come back to Los Angeles to adapt the novel into a screenplay.

Three years later, Blake had an Oscar.

The version we tell is about persistence. The real story is stranger. The man whose book was about to become one of the most celebrated films of the decade couldn’t keep a dishwashing job.

The thing we leave out: sometimes the turning point isn’t visible. Sometimes you get fired from the worst job you’ve ever had the same week your life changes, and you can’t tell which one matters.

Story 2: The man who invented Tetris and didn’t see a dollar for ten years

Alexey Pajitnov built Tetris in 1984, in a Soviet research center, on a computer that could barely render the blocks. It was a side project.

The game was so addictive his coworkers couldn’t stop playing it. It spread on floppy disks across research institutes, then across the Eastern Bloc, copy to copy, no money changing hands.

Then it leaked to the West.

What followed was a decade-long licensing war involving Atari, Nintendo, a Soviet agency called ELORG, and a cast of people who didn’t fully understand what they were negotiating.

Here’s what’s not in the movie version.

Pajitnov didn’t earn a single ruble or dollar from Tetris for the first ten years. Not because he was cheated. Because under Soviet law, ideas created on state time belonged to the state. When ownership came up, he signed the rights over himself for ten years. He later said he just wanted things to go smoothly.

By the time Nintendo bundled Tetris with the Game Boy in 1989, the creator of the game was still a salaried researcher in Moscow. He likely lost tens of millions in royalties.

I got my first Game Boy in 1991. Tetris was the only game I played. On a flight from Boston to LA, I played from boarding to landing without stopping.

That same year, Pajitnov was leaving Moscow for the United States. Five more years before the rights reverted to him. Six before he started collecting royalties.

And here’s the part I keep thinking about: he wasn’t bitter.

“I didn’t make much money at first, but I was happy, because my main priority was to see people enjoying my game.”

He co-founded The Tetris Company in 1996 and finally began earning from it. Twelve years after creating one of the most iconic games ever.

The version we tell is about inventors getting their due. The real story is that sometimes what you build outgrows you before you’ve figured out how to own it.

The thing we leave out: making something and owning something require different instincts. Most makers are much better at the first. Some never cared about the second.

Story 3: The inventor who was pushed out of his own company

Edwin Land founded Polaroid in 1937. He held 535 patents. Steve Jobs called him a hero.

The famous story is that Land invented instant photography because of his daughter. In 1943, she asked why she couldn’t see a photo right away. He went for a walk and sketched the system in his head.

The Polaroid camera launched in 1948. It sold out on day one. By 1970, the company had $500 million in revenue.

Here’s the part nobody tells.

In 1977, Land pushed Polaroid into a product called Polavision, an instant home movie camera. His friend Akio Morita warned him it was too late. Video technology was already arriving.

Land didn’t listen.

Polavision failed. Polaroid wrote off $89 million. By 1980, Land stepped down as president. In 1982, the board forced him out. He sold his shares in 1985.

And then, the detail that stays with me.

When Land died in 1991, his family destroyed his personal papers. Notes, correspondence, unpublished work. He didn’t want to be remembered as a man. He wanted to be remembered as the work.

The version we tell is about a visionary. The real story is about a maker who stayed a maker in a role that required something else.

The thing we leave out: keeping what you built, across time, across shifts, across your own changing judgment, is a different problem. And it may be the hardest one.

Three problems, one hunger

Blake couldn’t hold a dishwashing job the week his life turned. Pajitnov gave away his creation for a decade and didn’t seem to mind. Land built a company and was pushed out of it.

None of that fits the motivational version.

But the uncut versions are more useful.

Blake solved making. Pajitnov solved making and was fine never owning. Land solved making and owning, and lost keeping. Each of them got one or two of the three. None of them got all three. And the ones we call “failures” often just failed at a problem they were never trying to solve.

And underneath all of it is the question almost nobody asks: which hunger are you feeding?

The stories you’re told are always about the making. But that’s only part of it.

The people who last are the ones who figure out when their hunger has changed, and adjust. The ones who don’t get trapped by it, even when they’re winning.

I know the keeping problem from the inside.

I spent nine years building a company. In 2012, during the Greek crisis, I signed a deal I knew was wrong. I knew what the outcome would be. The company needed the cash flow to survive, and I needed the company to survive so my people could keep their jobs. With more than 50 people working for me, I felt the weight. It cost me control of my company. I moved back to Boston not long after.

I tell you this because the three stories aren’t something I’ve read about. I’ve lived one of them. It cost me more than I expected, but I’d do it again anyway. That doesn’t mean it’s settled. The years after were difficult enough that I’ve wondered, more than once, whether I should have been the kind of person who looks out for himself first. I’m not sure there’s an answer to that.

That’s what makes the keeping problem the hardest of the three. Sometimes the only way to keep the thing is to give it up. Or you could do what Larry, Sergey, and Zuck did — with 10x voting shares 😁

Now, I'm building a company called Inkjin. I want it to be my forever company. That’s something I couldn’t have said at twenty-five.

The funny thing is that I only have one tattoo (it's my wife's name in her writing). I got it a few years before starting the company. I never thought I'd be building a tattoo company. My co-founders and my kids have more than fifty tattoos between them.

I’m not building Inkjin because I’m a tattoo guy. I’m building it because the people I love are, and I saw a problem worth solving for them.

The hunger that got me here isn’t the one that bought the Converse. It isn’t the one that put Onassis on my wall. It isn’t the one that would have said yes in 2011.

It’s quieter.

It’s about the build. About putting something useful in someone’s hands. About watching the thing you made get used by the people you made it for.

You can be right to build something, right to leave it, and right to walk past it when it comes back. All at once. Still true years later.

Sometimes the only reason that’s possible is that the hunger changed, and you let it.

Those are the stories I pay attention to now.

I’ve stopped raising for a while now.

I want to say that out loud because last year I was doing the opposite, and I was forcing it.

I was pushing hard. Too hard. Hard in a way that, looking back, had a smell to it. The smell of a founder who’s stopped building and started performing. I was on the road. I was in the meetings. I was telling the story over and over until the story started running me instead of the other way around. And I could feel, not all the time, but in the quiet moments between meetings, that I’d drifted into something that looked like desperation even though I was pretending it wasn’t.

Desperation has a smell. People can pick it up before you’ve finished the second slide. I know this because I’ve been the one across the table, and I know it because I was the one giving off the smell and lying to myself about it.

Toronto

The hinge was Toronto.

In the fitst week of October we went out for a week as part of Accelerate Greece. Good program. Real meetings. The kind of stretch where you think you’re going to come back with momentum, and instead you come back with clarity, which is a less comfortable thing to come back with.

Somewhere in the middle of that week I looked around and saw the company the way an investor would see it, not the way I’d been describing it. And the gap between those two pictures was bigger than I’d been letting myself admit.

We weren’t ready. The team. The company. We hadn’t earned the speed that money would have forced on us. We hadn’t grinded long enough to be the version of ourselves that walks into that next stage and handles it instead of being handled by it.

That’s not a story about anyone falling short. It’s a story about timing. About a founder, me, who was trying to skip a chapter we still needed to write. About a company that was further from ready than its founder was willing to say out loud, and about a team that deserved a leader who wasn’t dragging them into a stage they hadn’t had the chance to grow into.

We needed to grind more. We needed to get the company into a better position. The investors who passed on us last year weren’t wrong about all of it. We didn’t have enough traction. We didn’t have revenue. Some of them didn’t get the tattoo market and never were going to, but that’s a different story. But on the readiness question, they were calling something I should have called months earlier.

I came back from Toronto and started letting the fundraise die.

Not in one dramatic decision. Just a series of small ones, just letting the silence settle and noticing that the silence felt better than the noise had.

The Quiet After

Here’s the part nobody tells you about pulling back from a fundraise.

The first week feels like failure.

The second week feels like relief.

By the third week you realize you’ve been doing two jobs and pretending it was one, and you start to feel something shift in your chest that you hadn’t realized was clenched.

When I stopped pitching, I got my company back.

We’ve spent the months since doing the things that actually matter at this stage. Building more product. Expanding into new geographies we’d been talking about for a year and never moved on because there was always another investor meeting, always another follow-up email, always another reason to keep the second job running. Getting closer to the people we’re building for. Building revenue streams. The quiet stuff. The stuff that compounds and eventually makes you undeniable.

We found our equilibrium. That’s the word that keeps coming back to me. Not momentum, a word startup people like because it sounds like you’re making progress and makes you feel like you’re winning. Equilibrium. The rate at which we can build something real without trying to make it look bigger than it is.

I’ve raised before. I know what money does and what it doesn’t do. Money buys speed. That’s the whole pitch when you strip away the rest of it. Money buys speed.

The question I had to actually sit with after Toronto was whether we needed to go super fast. And the honest answer was no. We don’t. The thing that would actually kill us isn’t moving slowly. It’s moving fast in the wrong direction, one we hadn’t earned the right to move in.

Three Posts, Same Conclusion

A couple of weeks ago, I came across three posts from David Yi that articulated the structural version of what I decided.

They didn’t change anything. The decision wasn’t on the table anymore. But it was strange to read someone else, from the investor side of the room, landing on the same conclusions I’d already been operating under for few months now.

The first one was about the best founders starting to ignore VCs. The argument is that capital used to be required to start, and it isn’t anymore, not for most categories. The cost of building has collapsed. Distribution doesn’t require paid spend the way it used to. You can run a real business with a small team. So why would you trade away the most valuable thing you own for cash you can generate yourself? The sequence used to be raise, build, distribute. The new sequence is build, distribute, and then decide if you even want to raise.

The second one was about the worst time to raise being the moment you actually need the money. That one stung when I read it, because that’s exactly the wall I’d been drifting toward last year. Desperation has a smell. Your urgency becomes their leverage. Your timeline becomes their control. The founders who raise easily are the ones who don’t need to. Everyone else gets eaten by the gap between what they need and what they’re worth in a room full of people who can sense the difference.

The third one was about angels, most of them being tourists, not investors. Chasing hype rounds. Writing checks at the idea stage with no signal to read. Wondering why nothing compounds. The angels who actually generate returns are close enough to the founders and the businesses to see what others miss before there’s a narrative to attach to it. Proximity. Pattern recognition. Being useful beyond the check.

That last one is the one I think about most. Not as a critique of angels. As a description of who I want when we do open a round again. People who are around when I need something. People who get the market. People who are active angels and have written a few checks before we came calling.

Those people exist. They’re rarer than the tourists. You find them, or they find you, by building something real, long enough, that the right people start paying attention.

Why This Is the Right Move

I believe in what we’re building. I believe in the problem. I believe the market is bigger and more interesting than the people who passed on us were able to see, and I think part of why they couldn’t see it is exactly the reason we should be the ones building it. I believe in my team, and the work we still have to do together.

What changed isn’t the conviction. It’s the timeline.

Last year I was operating on the implicit assumption that we needed to move at venture speed, which meant we needed venture money, which meant the calendar was being set by people who weren’t us. This year I’m operating on the assumption that we need to move at our speed. Which is the speed at which we can build something good without ovestating things we haven’t earned and without forcing the company into a stage we haven’t grown into yet.

We’re going to keep building product. We’re going to keep expanding into new geographies. We’re going to get closer to the people we’re building for. We going to keep building pur revenue. We’re going to let the business compound on its own terms, the way businesses actually grow, when you stop interrupting them every six weeks to fundraise.

Raising money matters. Raising it from the right people matters more. There’s a version of capital that compounds with you, that gets sharper the longer it sits on your cap table, that asks the right questions and shows up when things are hard. And there’s a version that just sits there, or worse, pulls against you. The difference between those two versions isn’t the check size or the brand on the term sheet. It’s whether the people writing the check actually understand what you’re building, believe in why it matters, and are aligned on the kind of company you’re trying to build.

When we raise, it’ll be from the right investors, on our terms. Not because I’m playing hard to get. Because by then the math will work that way. Because the company will be undeniable enough that the conversations are different.

Until then, the answer to “are you raising?” is the one I should have been giving a year ago.

Not right now. We’re building.

Startups were built for people. So was the web. The trouble is that they’re still being built just for people.

The web we know was designed for human attention. Landing pages, conversion funnels, forms, and interfaces were designed to get people to take action. What doesn’t make sense anymore is thinking that’s enough. The next web will be designed for agents, but not chatbots and copilots, rather agents that can infer intent, compare choices, filter noise, and take action on a user’s behalf.

In an agentic world, the question isn’t whether another human can understand your business. It’s whether another machine can. Can it figure out what you sell? Who it’s for? How it compares? Can it validate prices, inventory, reputation, and outcomes, then act without getting tripped up in vagueness or fine print?

Most startups can’t.

They look nice on the surface: nice website, nice deck, nice branding. But the deeper they go, the more things get fuzzy. Services are underspecified. Prices are hidden. Policies are inconsistent. Knowledge is locked up in Slack threads and Notion documents. No agent can make sense of that soup.

Humans can. Agents can’t. That’s the reality.

Most startups still get away with it because humans are willing to work around the slop. Agents won’t.

The web we know is about capturing human attention. The web we’re building is about being machine-readable. Startups must become legible, structured, explicit, accessible, not just beautiful.

It starts with facts. Not your mission or your manifesto. Just the facts. What you offer. For whom. At what price. Under what terms. With what next step.

Humans can read between the lines. Agents can’t. They need structure, metadata, and defined states. If your startup still thinks of its web presence as a brochure, you’re behind the times already.

But clarity is only half the battle. In an agentic world, questions of trust get pushed upstream. When a user delegates a choice to a piece of software, that software must have a way to decide whom to trust. Reviews, identity verification, policy clarity, and fulfillment consistency all become features of a machine’s model of trustworthiness.

Some founders will treat this as a problem of discovery: how to get found by agents. But it’s a problem of trust and execution disguised as a problem of discovery.

Agents won’t just recommend. They’ll filter, constantly, quietly. They’ll favor the clear, the verifiable, and the consistent.

So ask yourself: Is your data up to date? Is your availability accurate? Are your service boundaries clear? Can another system do business with you without a human intervening to explain how things “really work?”

If not, your startup is “visible” to humans but “invisible” to machines.

This same imperative, for clarity, structure, and consistency, extends into every corner of how startups communicate, get discovered, and stay relevant.

Content Becomes Infrastructure

This same transformation is playing out in content. Most people think about AI for content as a question of speed. How can I write faster? Edit faster? Post more? That’s the superficial read. It’s real. It’s useful. But superficial.

The deeper read is that content is moving from standalone content to networked infrastructure. Research, ideation, scripting, reuse, distribution, testing, and optimization don’t need to be separate tasks anymore. Networked agents can handle them fluidly, from a shared understanding.

This shifts what content is for.

Content isn’t just for marketing anymore. It’s also for getting your business recognized by humans and machines, for aiding discovery, for bolstering trust, for building memory, for defining your category, for teaching your market what you do, who you serve, and why you matter. And increasingly, for giving AI agents more data to understand, compare, and act upon your business.

This matters because in a world of agents, silence is expensive. If your company isn’t generating structured, relevant, high-signal content, you’re leaving a vacuum that others, and their agents, will fill.

But the solution isn’t to flood the web with junk.

The opportunity is to develop a system that turns insight into content, content into distribution, and distribution into learning. A system that doesn’t just produce content but learns from the signals that content sends back: what gets clicked, what gets quoted, what gets shared, what gets ignored, what leads to trust, and what leads to action.

This is why content is much closer to product and operations than many founders realize. It’s not a layer you add on top anymore. It’s part of your business’s operating system.

In the last decade, content supported growth. In the next one, it will help determine whether your startup is seen, understood, trusted, and chosen at all.

From Prompts to Systems

Recently, we started using OpenClaw at Inkjin to automate aspects of the business with agents. We plugged it into Claude Max 5 and ChatGPT and began training it on Inkjin so it grasps our product, market, and positioning. It already helps with competitor tracking, research, and content suggestions based on what’s occurring in our space.

In the middle of that shift is our AI agent Artémis. It is the first step from intent to action, helping organize ideas, questions and doubts into more precise requests, more relevant suggestions and quicker decisions. It represents the kind of product we want to build: a product that can understand the context, reduce the noise and just make the next step simple.

That might sound like a productivity hack. It’s more than that.

Once you hook AI up to actual processes, you stop thinking in terms of prompts and begin thinking in terms of systems. You stop asking “What can I ask it?” and begin asking “What should this system know, what should it decide, what should it do, and how should it get better over time?”

That’s a different kind of leverage.

Founders who leverage AI like a faster intern will reap productivity rewards. Founders who use it to architect adaptive systems will build engines.

This creates both anxiety and leverage. Anxiety because “dirty” businesses will be exposed more quickly. Leverage because “clean” ones will be able to go much further with much less.

We feel this acutely in the booking flow. The customer almost never comes fully prepared to book. They come with inspiration, questions, disparate references, and partial info. This creates a lot of back-and-forth with the artists, delays decisions, and breaks conversions. This is where agents become valuable, not as content-generators but as systems that understand intent, structure the request, remove friction, match the right artist sooner, and inch the user closer to booking.

This is also true for content and distribution. We’ve created our Tattoo Guides, developed our backlink outreach to high-potential sites, optimized our on-page SEO, and integrated analytics and search tools. We’re not publishing content. We’re building a content engine.

Publishing is episodic. An engine compounds.

I was recently accepted into Founder Chapel's Inaugural Learning Pods, in particular the Media Blitz pod with Jay Jin on growing social media to 100+ videos a week with AI.

I’m looking forward to this because this isn’t a content dump. It’s about learning to think better, decide faster, and operate under pressure alongside other founders.

The timing for this feels exactly right.

Access to AI is no longer the hard part. Operational discipline is.

The real challenge now isn’t inspiration. It’s orchestration. How to move from ad hoc effort to repeatable systems. How to build workflows that hold up under pressure. How to turn content and operations into core business functions instead of side work you squeeze in when you have time.

A pod about producing 100+ videos a week with AI may sound like a media tactic. But it’s really a lesson in systems. It’s about moving away from bursts of effort to repeatable production without chaos.

That is exactly the shift founders need to make.

What an Agent-Ready Startup Looks Like

In an agentic world, your startup can no longer be just a product or a website. It has to become a system other systems can understand, trust, and act through.

That touches everything: a clearer business model, more transparent operations, explicit pricing, visible trust signals, compounding content, and workflows that agents can actually navigate.

AI can’t save a business held together by ambiguity. Agents don’t care how good your design is. They care how clear your logic is.

That’s the opportunity.

Small, structured, legible startups can outperform larger, messier incumbents. Agents don’t optimize for brand prestige. They optimize for clarity, reliability, and follow-through.

So don’t ask only how your startup looks. Ask how it reads. Ask whether another system, not a person, can find you, trust you, and act through you.

Because in this next era, clarity isn’t just good design. It’s survival.

I opened my old blog. I knew the blog existed, I didn’t realize how active it had been. Then I saw the number: 734 posts.

They were sitting in a Tumblr export from a blog I started in 2004, first called Buzz, later Endeavour. I hadn’t opened it in years — not while building companies in crypto, not while launching Inkjin, not while writing this newsletter.

734 posts.

I started scrolling.

Early posts in Greek about digital advertising. Posts in English about startups. Hiring announcements for companies I no longer run. A tribute to Steve Jobs from 2011. A post about my son turning 17. A two-sentence post from 2013: “Fail, Fail, Fail… (maybe) Win!”

All of it written by me. Most of it forgotten by me.

That’s just one platform. Add two Substacks, Daily Fintech, Medium, LinkedIn, and 8,000+ tweets, and I’ve published over 9,000 pieces in 22 years. More than 800 of them are articles and blog posts.

I didn’t plan that. I didn’t understand what it meant until now.

In 2015, I wrote a short post: “Timing is Everything for Startup Success.” A couple hundred words, referencing a talk by Bill Gross. The idea was simple — startups fail when the market isn’t ready.

Eleven years later, I wrote “Timing Is the Wind. Pacing Is the Game.” Same question. Different answer.

Not because I improved the original. Because I lived it. Built companies. Watched some catch the wind and others crash. Learned what happens when timing is right but structure is wrong.

I didn’t rewrite the idea. I re-lived it.

In 2016, I posted “33 Startup Lessons.” Just a list of short observations. Three years later, it became a Medium piece. In 2025, it became “Startups Don’t Die. Founders Quit.” Same lessons. Different weight.

The list became an argument. The observations became convictions.

That’s when it clicked. I’m not writing to publish. I’ve been writing to think.

Most people treat writing as output, something you do once you have clarity. I use it the other way around.

Writing is how I get there.

When I reached out to Bernard Lunn in 2017 to write for Daily Fintech, I wanted to dive deep into crypto. Writing forced me to read more, think harder, and form a point of view. Over five years, I wrote another 250 posts, publishing every Monday. Over time, those posts became a way to process a market moving faster than I could keep up.

Every post, even the short ones, the half-backed ones, the ones that went nowhere, was part of building a system. A way of processing ideas over time.

The early versions are thin. Incomplete. Sometimes wrong.

That’s the point.

Ideas don’t arrive finished. They show up as fragments: a sentence, a question, something unresolved. Then they sit there for years, collecting experience.

What you publish is just the first version that can stand on its own.

There’s something uncomfortable about reading your own work from twenty years ago. Not because the ideas are bad. Most of them hold up. Because the thinking is shallow. The posts are short. The arguments barely scratch the surface. The personal layer is missing. It’s watching someone learn to think on the page.

In 2009, I wrote: “Searching for the storyteller within myself.” I didn’t find it through technique. I found it through time.

Most of that Tumblr archive, 495 posts, is in Greek. That wasn’t accidental.

I was writing for myself. Trying to understand what was happening around me while building a company in Athens in the early days of digital. No audience. No distribution. No positioning. Just thinking, on the page.

Writing in Greek, for a small audience, about a small market looks irrelevant from the outside. It wasn’t. It was training.

Like building in a small market. The reps still count. The feedback loop is tighter. The thinking sharpens.

When you move to a bigger stage, you bring all of it with you.

I stopped writing publicly for almost two years. Then I came back. The writing felt different. Sharper. More direct. Less concerned with sounding right, more focused on being useful.

Nothing new had happened structurally. The system had just been running in the background.

Everything compounds. Even the quiet years.

Here’s the part most people miss. You think you’re writing posts. You’re not. You’re building the system that will think for you later.

Founders who don’t write reset their thinking every time. Same mistakes. Same shallow conclusions. No accumulation. Because nothing is being processed, captured, or revisited.

Writing fixes that.

This is easy to miss. You can build products, raise money, hire teams and still feel like you’re starting from scratch every time. Writing changed that for me. It made experience reusable.

I have 9,000 pieces of writing across 22 years. Most of them didn’t matter when I published them. All of them matter now. Because they built the thing underneath.

My real asset isn’t products or companies I’ve built.

It’s how I think. Writing built that.

Last week, Paul Graham wrote on X that churn is the worst reason to have slow growth. He was right. At that point, the problem is no longer awareness or friction at the top of the funnel. The problem is that users are getting in, experiencing the product, making a judgment, and leaving.

I learned what churn really meant in 2010 while building a group buying platform that eventually expanded into five countries.

When we started, we had almost no real competition. The model was still new. Merchants were curious, customers were excited about deals, and growth felt natural. Every new city we launched in showed the same early pattern—sign-ups grew quickly and merchants were eager to run promotions.

From the outside, it looked like a strong business.

But the market didn’t stay quiet for long.

Group buying quickly became one of the most competitive internet markets of that time. International players entered every city. Local copycats appeared overnight. Suddenly there were multiple deal platforms fighting for the same users and the same merchants.

That’s when the real behavior of the market revealed itself.

Customers weren’t loyal to any one platform. They were loyal to the best deal in front of them. One day they bought from us. The next day they bought from someone else. In a crowded market, the product wasn’t the platform. The product was the discount.

Merchants quickly realized this too.

Because there were so many competitors chasing deals, merchants started negotiating harder. Each one knew another platform would offer slightly better terms. Margins shrank. What once looked like a healthy marketplace slowly turned into a race to the bottom.

On the surface, the business still looked active.

But churn told the real story.

Users came for one deal and disappeared the next day. Merchants ran a campaign and then moved to the next platform offering slightly better economics.

That experience taught me something important: growth can look healthy while the foundation underneath is already leaking.

Acquisition can flatter a weak product.

Churn is the receipt.

When the Metric Stops Measuring Reality

Susan Montgomery, an angel investor I follow, recently shared an exchange that captures how founders sometimes misunderstand growth metrics.

A founder posted proudly that their company had reached $10 million in ARR.

That’s the kind of number that gets attention quickly.

Susan asked a simple follow-up question:

“How many customers churned in the last 90 days?”

The founder replied that they don’t track that number.

That answer says more than the revenue number.

You can’t really claim annual recurring revenue if you have no idea how much of that revenue is leaving is out the door. Without churn, ARR becomes a snapshot of contracts signed rather than evidence of a business that keeps customers over time.

This happens more often than people admit.

Founders optimize for the metric that sounds good in the fundraising deck—MRR extrapolated into ARR, contract value signed but not collected, pilot expansions that never convert.

At some point the metric stops measuring the achievement and becomes the achievement itself.

Revenue tells you what happened.

Churn tells you whether it lasts.

Not All Churn Means the Same Thing

Most teams treat churn as a single number on a dashboard. But churn usually comes in different shapes and forms, and each one points to a different problem.

Some users sign up but never reach the moment where the product’s value becomes obvious. They create an account, click around briefly, and disappear. This is activation churn. The user never crossed the threshold where the benefit of the product becomes clear. In many cases the product itself isn’t broken—the onboarding path simply failed to guide the user to value.

Other users do discover the value. They use the product for a while, sometimes enthusiastically at first. But gradually their usage declines. The product never becomes part of their routine or workflow. Over time it loses its place among the many tools competing for attention. This is engagement churn—a signal that the product works but lacks the depth to remain essential.

The most revealing form is deliberate churn.

These users understand the product. They used it consistently and experienced what it offers. Then they decided it wasn’t worth continuing.

One mistake founders often make is measuring churn using technical signals instead of behavioral ones.

Uninstalls, deleted accounts, or unsubscribed emails may look like churn metrics, but they rarely capture the real moment a user leaves.

Most people don’t delete accounts.

They simply stop using the product.

The real question is not whether someone uninstalled your app. The real question is whether they stopped getting value.

In practice, churn is best measured through behavior: users who were previously active but no longer take meaningful actions. They don’t return. They don’t engage. The product quietly disappears from their routine.

That silence is the real signal.

The Truth Hidden Inside Churn

The most uncomfortable reality about churn is that the people who leave often know the most about what needs to change.

Yet founders rarely talk to them.

Instead, they focus on acquiring more users, hoping that growth will eventually fix the problem.

Some of the most famous startup breakthroughs came from paying attention to the signals hidden inside churn.

In Airbnb’s early days, hosts were listing apartments but bookings were scarce. Brian Chesky and his cofounders visited hosts in New York and discovered something simple: the listing photos were terrible. Guests couldn’t properly see what they were booking.

Airbnb began helping hosts take better photos, and bookings increased almost immediately.

Coinbase experienced a similar moment. Early users were curious about cryptocurrency but found the platform confusing. Brian Armstrong noticed that people didn’t want complexity—they wanted a simple way to buy Bitcoin.

Adding that single feature unlocked growth.

Churn often reveals where the product experience breaks down.

Low acquisition means the market hasn’t judged you yet.

Churn means it has.

Users don’t write breakup letters. They rarely uninstall. They almost never delete their account. They just stop coming back. They stop taking action. They stop getting value.

That silence is the verdict.

And in business, silence is usually far more dangerous than criticism. Criticism means people still care enough to react. Churn means they’ve already moved on.

When I was starting out, I thought startup ideas arrived like lightning.

An idea would hit me, I’d feel the rush, and without much thought I'd convince myself I had found the one. Then I’d throw myself into building it. When it didn’t work, I had my excuses: people didn’t get it, the market wasn’t ready, everyone else was missing the obvious.

I was confusing excitement with opportunity.

Most ideas feel brilliant in your head. Very few survive contact with customers, timing, incentives, and distribution.

I get ideas all the time. I still write them down. But I don’t treat them as instructions anymore. Experience—and seeing hundreds of startup ideas over the years—has changed that.

Now I ask a different question.

Not, “Is this exciting?”
Is this real?

That’s the question that matters.

Because most people who want to start a company think they’re missing one thing: the idea.

“I don’t have an idea” is usually an excuse.

There are many ways to find startup ideas. Paul Graham has a simple, grounded approach: get close to a domain, notice what’s missing, and build from the problems you personally experience. Sometimes the best ideas aren’t even native to your field. They come from importing an insight from one domain into another.

When he helps founders, he often starts by asking what’s unusual about them: what do they know or care about that few other people do? And there’s a brutal filter that cuts through wishful thinking: could you build something that helps your peers make money? If yes, you’re probably looking at real demand.

That advice works because it pushes you toward reality.

But there’s another path to the same destination. Less romantic. More structural. And often more reliable.

Start With a Giant

Don’t start with yourself. Start with a market leader.

Pick a large incumbent in a meaningful category. The kind of company that looks impossible to beat. Then stop thinking about their strengths and start studying their constraints. Because every dominant product is optimized around a core customer. Their roadmap, pricing, positioning, network effects, propriatery data and UX aren’t random — they’re designed to protect the segment that pays the bills and defines success internally.

Start by reading their reviews and support forums, not their marketing. Look for complaints that repeat but never get fixed. Then map who’s complaining: are they a non-core segment? Finally, ask why the incumbent won’t solve it. If the answer is “it would confuse the core user,” “it breaks pricing,” or “it threatens the bundle,” you’ve found a real wedge.

Then ask a second question: what changed recently that makes a new experience possible now? Many great startup ideas combine something that has always been needed with something that has only recently become possible.

Sometimes the shift is technological. Sometimes it’s behavioral. Sometimes it’s infrastructure. But when a real wedge meets a real enabling change, the opportunity becomes much stronger.

Optimization Is the Trap

That optimization is their advantage. It’s also their trap.

The hard part isn’t finding the wedge. It’s keeping it. The moment you broaden to please the mainstream user, you start inheriting the incumbent’s compromises—more complexity, muddier positioning, slower decisions. The wedge only works if you stay narrow long enough to dominate the edge.

I’ve seen this pattern repeatedly: the opportunity was never hidden. It was just structurally inconvenient for the leader.

Once a company locks into serving its core, the edges of the market become awkward. The beginners who feel overwhelmed. The niche professionals with specific workflows. The customers with different levels of price sensitivity. The teams who want a different experience entirely.

Most edge segments are small. The bet is that they’re concentrated, underserved, and capable of expanding.

Serving them properly often comes with a cost the incumbent doesn’t want to pay. It can confuse the main user. It can clutter the product. It can dilute positioning. It can break pricing. It can create cannibalization. In other words: the incumbent can’t fully commit to that segment without complicating, cannibalizing, or weakening the core.

So the edge gets partial attention. Half-features. Side projects. “Maybe later.”

That gap is your wedge.

If the incumbent could fix it with one sprint and a pricing tweak, it’s not a wedge.

Win the Edge

A clean example is Figma versus Adobe.

Adobe wasn’t weak. Adobe was optimized: desktop software, powerful tools, file-based workflows, and a business model built around Creative Cloud bundles and enterprise contracts. Real-time, browser-native collaboration wasn’t a simple add-on. It implied a different product philosophy. A different workflow. A different distribution story. A different future.

Could Adobe have built collaboration features? Sure. But going all-in on browser-first collaboration would have required Adobe to reorganize around a future that threatened parts of its past. Big companies don’t ignore these choices. They avoid them.

Figma had no legacy to protect. No desktop revenue to defend. No bundle to preserve. It could commit fully. Collaboration wasn’t a feature. It was the product. Multiplayer in the browser by default.

What was strategically complicated for Adobe was existential for Figma.

A similar pattern played out with Shopify and Amazon. Amazon is optimized for the marketplace: customer ownership, standardized experiences, and keeping buyers inside Amazon. Independent merchants wanted the opposite—control, brand, and a direct relationship with customers. Amazon can’t fully optimize for merchant sovereignty without weakening its own marketplace model. Shopify made that sovereignty the product.

Another useful habit is simply watching where new companies are emerging.

I like to look at the companies in recent startup accelerators or YC batches. Patterns appear quickly: founders refactoring developer tools, verticalizing fragmented industries, or building infrastructure for new technologies. Often the next set of ideas is already visible in the experiments of the these early-stage startups.

That’s the pattern you’re looking for.

The edge isn’t the destination. It’s the beachhead.

You don’t win by outbuilding the incumbent across the whole market. You win by taking the thing they can’t treat as primary and making it your entire identity.

You build the standalone product that serves the edge segment cleanly—with their language, their workflow, their priorities—and you refuse to compromise for anyone else.

Not every wedge is yours to win, though. Founder-company fit matters. The opportunity has to match something you understand deeply enough to see clearly and pursue for years.

Win the edge first. Then expand inward.

If the incumbent gives that segment 5% attention and you give it 100%, you move faster by default. You listen harder. You simplify more aggressively. You build a product that feels inevitable to the people who were ignored, because it finally fits them.

Focus Where They Can’t

So if you want to start a company and you don’t have “the idea,” stop staring at a blank page.

Go find a giant. Find the customers they’re structurally unable to love. Find the thing they can’t ship without hurting themselves.

Then commit to it harder than they ever can.

When your entire company is built around what they treat as an option, you don’t need to beat them everywhere.

You only need to win where they can’t commit.

You’re no longer competing on resources.

You’re competing on focus.

Most founders think investor meetings are about the product. They’re not.
They’re about judgment under uncertainty: how you think, how you operate, and what you do when the story stops being fun.

This cycle has made it impossible to miss: in the AI market, some of the biggest seed rounds are being priced on founder track record and team—well before revenue, and sometimes before a shipped product.

Here are eight dynamics investors use, consciously or not, to decide if you’re fundable and worth backing.

1) Safe Mess vs Fatal Mess

Startups are messy. The only fatal mistake is confusing cosmetic chaos for structural decay. Investors aren’t scared by duct tape. They’re scared by founders who can’t diagnose what’s actually broken. The tell is simple: when you describe the business, do you talk about symptoms (“we need marketing”) or causes (“retention drops after day 3 because setup is confusing”)? The punchline: if you can’t separate safe mess from fatal mess, you’ll spend the round fixing the wrong things.

• What it signals: Whether you can tell cosmetic chaos from structural decay.

• What works: Name the mess, rank it, and show the weekly plan. “Ugly onboarding is fine. Churn we can’t explain is not.”

• What kills it: Either panicking at everything or pretending nothing is wrong.

• The deeper point: Investors don’t fund “polish.” They fund judgment. If you can’t tell the difference between a surface mess and a structural problem, you’ll spend the round cleaning surfaces while the foundation cracks.

2) Borrowed Conviction

“Who else is investing?” is often a shortcut for outsourced thinking. Some investors want truth; others want cover. The real-world behavior is predictable: they’re enthusiastic only after a credible name commits, and vague before that. Social proof can accelerate a decision, but if it’s required for the decision, you’re not raising, you’re waiting for someone else to validate you.

• What it signals: Whether an investor is thinking or asking for permission to believe.

• What works: Give clean facts, then pivot back to fundamentals. “€X committed from relevant operators. We’re allocating the last €Y to additive angels.”

• What kills it: No signal (“still building”) or fake signal (irrelevant name-dropping).

• The deeper point: Social proof compresses timelines. It doesn’t create truth. If the only reason someone invests is because another investor did, you don’t have enough conviction.

3) Tempo Is a Tell

Fundraising is a live demo of how you run everything. Investors don’t just listen to your plan, they watch whether you can execute a process: clear steps, clear timing, clean follow-ups. The consequence of “we’re flexible” isn’t just slower fundraising. It’s a round that stretches, drains the team, and forces worse terms because time becomes your enemy.

• What it signals: Your fundraising process predicts how you’ll run the company.

• What works: A real deadline + a real cadence. “Closing in 4–6 weeks. Dataroom ready. Weekly updates. Decision window.”

• What kills it: “We’re flexible.” Flexible = drift = no leverage.

• The deeper point: Tempo is leverage because time is never neutral. A tight process forces decisions while you still have options. A loose process drags you into need, and need rewrites every term against you.

4) Don’t Price Yourself First

Valuation is where founders accidentally give away leverage, either by anchoring too low or by turning the meeting into a negotiation before belief exists. The tell is early defensiveness: once a number is on the table, every question sounds like an attack. The punchline: if you can’t keep the conversation on fundamentals, you’ll optimize for winning the price instead of winning the round.

• What it signals: Whether you’re building conviction or negotiating before belief exists.

• What works: Sequence it: fit first, terms second. “Let’s decide if we should work together, then we’ll discuss terms.”

• What kills it: Leading with valuation and turning the meeting into haggling.

• The deeper point: Price follows conviction. Not the other way around. Start with price and you invite negotiation; start with the fundamentals and you build belief. One turns the round into haggling. The other turns it into momentum

5) Money Has a Personality

The “wrong money” doesn’t just cost you peace. It costs you options. The tell is how you feel after the call: energized or uneasy. Because once they’re on your cap table, they’re in the room on hard decisions, down rounds, key hires, and exits. The punchline: their “connections” won’t save you, but their character can sink you.

• What it signals: Whether you’re optimizing short-term access over long-term reputation.

• What works: Take money from people you respect and would want in the room on bad days.

• What kills it: Rationalizing a bad partner because they promise connections.

• The deeper point: The investor‘s magic rolodex will decrease exponentially as you continue to work in the industry and grow your own connections — a year later it will hardly matter. But they’ll still be a pain to deal with.

6) Candor Wins Trust

This is not diagnosis. This is disclosure. Investors assume problems exist; they’re judging whether you’ll tell the truth when it’s uncomfortable. The real-world behavior: confident founders volunteer the bad news early before being asked, because it signals control. The consequence of hiding issues is brutal: investors don’t think “they’re doing great,” they think “what else aren’t they telling me?”

• What it signals: Whether you see reality and tell the truth under pressure.

• What works: Calm specifics: risk → cause → learnings → next experiment.

• What kills it: Hiding problems or speaking in fog.

• The deeper point: Hiding problems doesn’t make you look stronger. It makes you look unsafe. Investors can live with risk, but they can’t live with surprises, because surprises are how trust dies.

7) Plain English or Bust

Marketing language is a tax on trust. The tell is when investors ask three times “so who is this for?” because your description never lands. The consequence is deadly: if they can’t repeat your pitch to a partner, you don’t move forward.

• What it signals: Clarity of thought and ability to prioritize.

• What works: “We do X for Y so they can Z,” plus one sentence on why it’s hard.

• What kills it: Buzzwords and grandiose positioning that needs decoding.

• The deeper point: Plain language isn’t simplicity for its own sake. It’s proof you understand the system well enough to compress it. If you can’t say it clearly, then you don’t understand it and execution will follow the same fog.

8) It’s a Bet, Not a Promise

Investors don’t need inevitability. They need a rational bet. The tell is whether you understand the bridge from here to the next round: what must become true, by when, and why you can get there. The punchline: capital doesn’t create growth, it accelerates it. If users don’t love the product, you’re not funding a company. You’re funding denial.

• What it signals: Whether you understand the actual investor calculus: upside × probability × price.

• What works: Show the shape of the win and the path: wedge, distribution, compounding advantage, milestones to next round.

• What kills it: “Money will fix growth” thinking and hand-wavy inevitability.

• The deeper point: Investors aren’t buying certainty. They’re buying asymmetric upside at a price that makes the risk rational. Your job isn’t to guarantee the outcome, it’s to show why this risk is worth taking at this price.

This cycle is reminding everyone: some checks are written on pedigree, not just fundamentals. Either way, the underwriting logic doesn’t change. These 8 dynamics are the checklist.

If you’re raising, print this and keep it next to your dataroom. If you’re an investor, you already run this checklist, whether you admit it or not.

Have a great March—clear thinking, tight process, no noise.

In Greece, we fly kites on Clean Monday. It marks the beginning of Lent — a symbolic reset, a tradition symbolizing a fresh start and spiritual uplift.

As a child, I didn’t think about symbolism. I only cared whether my kite would rise. It didn’t rise because it was beautiful. It rose because tension was right.

That lesson applies to startups more than most founders realize.

“Bad timing” is one of the most common explanations for startup failure. It is also one of the least examined.

Founders say they were too early. Investors say the market wasn’t ready. The company shuts down, and the diagnosis feels complete.

Bill Gross once argued that timing is the single most important factor in startup success. Markets shift. Technology matures. Behavior evolves. Companies rise on those waves.

It’s a compelling thesis. And it is incomplete.

Timing is real. But it is not an independent force acting on a startup like weather. Timing is the wind.

But startups do not fail because there is no wind. They fail because they mis-handle tension.

If you have ever flown a kite, you understand this. You can stand in a windy field and still fail. Wrong angle. Too much slack. Too much tension. Too much weight. In strong wind, a fragile kite does not drift lower. It snaps.

Markets behave the same way. Some markets are small and stagnant. There is no lift. Some are large but matured. The air is thick with incumbents. Some are small and will grow, just not yet. And some are small and accelerating rapidly. That is when fundraising, hiring, and distribution feel effortless.

Wind speed varies by market phase.

But even in strong wind, not every kite survives.

When online video became viable, YouTube was not alone. When social networking reached critical mass, Facebook entered a world where Friendster and MySpace already had lift. Infrastructure was shared, but durability was not.

When Pinterest, Instagram, and Snapchat came around in 2010 and 2011, respectively, it seemed like the social space had been won by Facebook, Linkedin and Twitter. But all three enabled new use cases: Pinning articles from the web, sharing filtered photos, and disappearing messages, features that made sense on their own and weren’t offered by the incumbents. I think that all three of these players just barely squeezed in, but it validates that investing in a market like this sometimes works.

If timing were decisive in isolation, outcomes within the same window would converge. They don’t. The missing variable is pacing.

A Gust Is Not a Climate

Timing reduces friction. Structural shifts (technology, regulation, distribution, behavior) increase wind speed.

Smartphones unlocked ride-sharing like Uber. Cloud infrastructure lowered startup costs and eliminated distribution barriers that constrained early video platforms. Social identity normalized trust among strangers and lowered resistance for Airbnb.

These shifts create market pull. Customer acquisition becomes easier. Demand feels organic.

Wind increases.

But founders do not experience “timing.” They experience signals: rising signups, declining acquisition costs, viral spikes, abundant capital.

The danger is confusing weather with climate. A gust feels like lift. It isn’t always.

AI is the latest wind. In 2025, roughly half of global venture funding flowed into AI — more than $200 billion, up sharply year over year. Capital is abundant. Valuations are aggressive.

A large majority of enterprise generative AI pilots fail to produce measurable returns. Early-stage AI startups fail at rates comparable to prior hype cycles, even as funding accelerates.

When capital tightens, the distinction between temporary lift and structural economics becomes clear.

Timing can mask fragility.

Market pull compresses friction. It does not eliminate structural weakness.

I learned this firsthand. In the spring of 2010, I launched Tsoonami, a daily deal platform, and scaled across five countries. The wind was still strong. Consumers wanted discounts. Merchants were experimenting. Email and social distribution were inexpensive. Expansion felt inevitable.

But underneath the growth, the weaknesses were visible: merchant fatigue, thin margins, limited repeat behavior, rising acquisition costs. What looked like durable lift was partly momentum. When novelty cooled and competition intensified, the economics tightened quickly.

The idea wasn’t wrong and the wind was real.

But it amplified fragility as much as it amplified growth.

The Chasm Is Financial

Timing is not about launching before or after an invisible switch flips. It is about rate of change.

Specifically, it is about whether your burn rate and learning speed match the market’s adoption curve.

Everett Rogers wrote the landmark book Diffusion of Innovations in 1962, describing how innovations move from early adopters to the early majority (known as the “Bell Curve of Innovation”). Between them lies a gap, the chasm, where enthusiasm slows and proof becomes mandatory.

Most startups die in that gap.

Not because the idea was wrong. But because the company cannot survive the distance between early excitement and mainstream validation.

An 18-month venture runway can expire just before the market inflects. From the outside, that looks like “bad timing.” In reality, it is a mismatch between burn and market phase.

Timing kills startups when cash runs out before clarity arrives. The chasm is not psychological. It is financial.

Burn must outlast doubt.

Timing Is a Sequencing Problem

Most timing failures are cost–revenue sequencing failures.

Hiring aggressively before validation. Scaling sales before retention stabilizes. Paying commissions before collecting cash. In each case, costs accelerate before revenue becomes durable.

These are not macro errors. They are structural mismatches between burn and proof.

Being early is survivable if you are built to wait. Narrow scope. Controlled burn. Fast feedback loops.

Conversely, a startup can launch into genuine market pull and still fail if it scales as though validation is permanent. The difference is not the wind. It is how much tension the structure can absorb.

Markets move at their own speed. Paradigm shifts accelerate adoption, but they do not eliminate uncertainty.

You do not need to predict the exact moment when the market turns. You need to structure your company so it does not require the market to turn quickly.

The wind is neutral. Operator quality is not.

Timing makes flight possible. But staying airborne depends on whether you built something that can survive the distance between possibility and proof.

Sales matter in early-stage startups because they answer one urgent question: will someone pay.

But founders often over-celebrate the answer.

A few years back, I was mentoring a company that hit its first nine months of revenue exactly to plan. The early orders came through friends in the industry and personal connections. On paper, everything looked promising. With targets met, they scaled — seven in sales, three in marketing — hiring against a model that felt validated.

Then reality surfaced.

Those early orders hadn’t required the company to deeply understand its customers. There had been no real discovery. No clarity on why customers bought. No repeatable sales process. Marketing was rewriting messaging weekly. Sales was active but directionless.

The founders had confused early transactions with product-market fit.

The mistake wasn’t effort. It was interpretation. Early revenue can feel like proof. Sometimes it’s insulation.

A sale tells you the risk felt acceptable in that moment. Maybe your pricing worked. Maybe your positioning landed. Maybe the timing was right. But a sale does not prove belief. It proves that curiosity cleared a threshold.

That proof shows up later.

The Pattern

The real signal is repetition. When a customer returns without being pushed, something more durable is happening. The product delivered. Expectations were met. The experience held. That second interaction is where trust begins. Retention exposes truth. Acquisition hides it.

Founders gravitate toward the first transaction because it’s visible, measurable, and exciting. It feels like progress. It looks like traction.

But if growth weakens when spend slows, you didn’t build momentum. You built dependency.

Push creates activity. Pull creates gravity.

Pull shows up when users come back unprompted. When the product spreads through usage. When sharing increases value instead of merely advertising it.

This is why retention matters more than acquisition in the early stages. Acquisition proves reach. Retention proves relevance. One shows you can attract attention. The other shows you can hold it.

Trust accumulates quietly in the second and third interactions. It compounds through consistency, not campaigns.

It shows up in renewal rates, repeat purchases, declining friction, and unsolicited usage. It forms when onboarding clarifies instead of confuses, when reliability replaces novelty, when pricing still feels fair after the excitement fades.

If customers don’t return, scaling only amplifies confusion.

Without it, growth decays.

The Transfer

Brand begins when someone stakes their reputation on you.

Recommending your product means absorbing risk. If you disappoint, they pay socially. That decision is driven by repeated experience — not messaging.

This isn’t abstract.

In 2015, I mentored an Israeli company at MassChallenge in Boston that built a “social proof” platform. Their technology pulled real, organic conversations from social media and surfaced them directly on a brand’s website. No curated testimonials. No polished quotes. Just authentic user commentary — unfiltered reactions from real customers.

The founders understood something simple but powerful: people trust people more than brands. They weren’t trying to manufacture credibility. They were trying to surface it.

Word of mouth drives somewhere between 20% and 50% of purchasing decisions. Nearly 90% of consumers trust recommendations from people they know more than advertising.

That’s not a marketing statistic. It’s a trust statistic. And trust matters most when risk is high — when products are new, expensive, or complex.

But here’s what became clear during that mentorship: You can’t engineer word of mouth if the experience isn’t repeatable. You can surface it. You can amplify it. You can structure it.

But you can’t fake it.

People don’t share features. They share experiences. How it felt. Whether the promise held. Whether they’d risk recommending it.

Brand is distributed confidence. Marketing can amplify belief. Only repetition creates it. When customers talk about you without being asked, trust has traveled.

That’s the transfer.

Brand Is Leverage, Not Aesthetic

In the fall of 2019, I organized Brandhackers — a weekend hackathon where seven startups worked with a strategist, copywriter, and art director to rethink their branding.

Most founders showed up expecting better visuals. A sharper logo. A tighter tagline. Cleaner slides.

That wasn’t the real problem.

The teams that struggled weren’t unclear about how they looked. They were unclear about why customers would come back. When asked simple questions — Why would someone return? What changes after the second use? What would make someone recommend this? — the answers got vague.

Branding exposed what product discovery had avoided.

The strongest teams didn’t leave with prettier decks. They left with sharper positioning rooted in repeat behavior. They understood which part of the experience created pull.

Brand wasn’t decoration. It was clarity about the pattern.

The exercise reinforced something most founders resist:You don’t build brand first. You build something worth repeating.

Brand is what forms around that repetition. It’s leverage earned through trust — not design layered on top of uncertainty.

The Compounding Effect

Founders love funnels because funnels feel controllable: More leads. More demos. More spend.

Funnels convert moments. They terminate at the transaction. But businesses compound through loops.

Use creates value. Value drives return. Return builds confidence. Confidence drives sharing. Sharing attracts better users.

Each cycle reduces friction for the next.

Premature scaling interrupts this discovery process. Hiring a sales team before finding repeatability doesn’t accelerate learning. It replaces it. You get motion in the field instead of insight. Activity instead of clarity.

Scaling before understanding is not speed. It’s dilution.

The Sequence

There is only one sequence that compounds: Sale → Return → Referral

First you validate willingness. Then you validate durability. Then you validate reputation.

If you’re not measuring second use and unsolicited referrals, you’re not measuring your business. If customers buy once, you have a funnel. If they come back, you have a business. If they tell others, you have a brand.

Founders often try to skip the middle. They mistake revenue for validation. They mistake activity for traction. They mistake hiring for progress.

But if customers don’t return, nothing else you measure matters. Sales get you paid. Trust keeps you alive. Brand gives you leverage.

Growth without repeat behavior is rented momentum. Build the pattern before you amplify the moment.

I see a lot of people posting lists of investors on LinkedIn who are “open to cold outreach.” Most of these lists are stale with recycled names, reshared endlessly, with little signal. The implication is that access is the bottleneck. Get the list. Send the message. Wait for replies.

That framing is comforting. It’s also wrong.

Most founders don’t fail at fundraising because they lack access. They fail because there’s no belief overlap.

Belief overlap isn’t abstract. It leaves traces. What investors write and speak about what they fund repeatedly, and how their portfolios move over time tell you far more than any “open to intros” list ever will.

Venture capital doesn’t run on persuasion. It runs on recognition.

Your pitch doesn’t create belief. It either fits into something an investor already believes or it doesn’t.

When what you’re building aligns with what investors already think will work, momentum feels natural. When it doesn’t, nothing really helps.

So don't feel bad when you don’t hear back or when you get rejected. It’s not personal. It's the default and it will happen 99% of the time.

How Investors Actually Decide

Before your second slide loads, an investor has already asked a few quiet questions:

• Have I seen this shape before?

• Does this market resemble something that worked?

• Does this founder look like someone who figured it out last time?

This isn’t laziness. It’s peeling the onion — managing risk under uncertainty.

When volume is high and certainty is low, decision-makers fall back on heuristics that helped them survive before: pattern matching, resemblance to past wins, and rules that prevented obvious mistakes.

Recognition starts before the pitch.

The deck is a compatibility test. And what gets tested isn’t just the idea. It’s how the founder thinks under pressure. How they frame tradeoffs. How they reason about risk. How they communicate. Whether their judgment feels familiar enough to trust.

Founders who resemble familiar success patterns tend to feel safer to back.

Investors form impressions almost immediately, before a single slide lands. Not based on what you say, but on whether you feel familiar—whether you resemble founders they’ve seen operate under pressure before.

This isn’t about charisma or performance. It’s pattern matching. Investors are quietly asking: does this person look like someone who can handle what comes next?

By the time the product is explained, that question is already in play.

The real question investors are assessing before and after your pitch is whether you and your startup feel like a risk they already understand.

Capital, Language, and Motion Tell the Truth

If you want to understand an investor, don’t start with their website. Start with their last ten checks.

There is a ton of data showing where investors actually place their bets—platforms like Crunchbase and PitchBook make funding history easy to track.

Investors and funds say many things publicly. Capital allocation is where belief shows up. Patterns repeat because repetition is safer. When a particular market, founder profile, or business model has worked, it becomes easier to believe in the next version of it.

This isn’t stubbornness. It’s rational behavior under uncertainty.

The same is true of language. When investors speak at length, on podcasts, in essays, on panels, they express what they believe.

“I care about distribution.”
“I avoid regulatory risk.”
“I prefer technical founders.”

These aren’t preferences. They’re filters.

You’re not there to change them. You’re there to see whether you already fit inside them.

Another signal founders miss is portfolio motion.

Funds show their direction through behavior before they explain it in words. When multiple portfolio companies start hiring the same kinds of roles, it’s usually not coincidence, it’s the fund quietly moving toward its next conviction.

Position yourself inside that motion and you stop looking like a new bet and start looking like continuity.

Where Founders Misread the Game

Founders experience timing as luck. Investors experience it as logistics.

Funds move through cycles: raising, deploying, supporting, reserving. Attention shifts accordingly. Silence doesn’t always mean disinterest. Sometimes it just means wrong timing.

Understanding this won’t make investors say yes. But it will keep you from misreading and burning leverage by pushing when alignment isn’t there.

The biggest mistake founders make is trying to teach investors a new worldview during a pitch. That almost never works.

Investors don’t want an education. They want to see whether a belief they already hold can take shape.

Look at the founders they’ve backed. Patterns show up quickly. Backgrounds repeat. Company shapes repeat. Ways of thinking repeat. This is what “fit” looks like in practice.

Founders assume investors are evaluating ideas in isolation. They don’t. They’re comparing what’s in front of them to a mental library of past decisions—some successful, some painful.

Your story should fit at the intersection of two things: what you’re building, and what the investor already thinks will work.

This is why two equally strong companies can get very different outcomes to the same pitch. One maps cleanly to a pattern the investor already understands. The other asks the investor to imagine a new one.

Mapping investor patterns is important, not to predict outcomes, but to reduce wasted motion and increase your chances. To avoid pitching people who were never going to say yes in the first place.

The Limit and the AI Trap

There’s a danger in taking this too far.

Founders are very good at turning side problems into main problems, especially problems that feel analytical. Modeling how investors think feels productive. It has structure. Inputs. Outputs. It creates a sense of control.

It’s also much easier than the harder work: making something people want badly enough that investors feel uncomfortable saying no.

Fundraising becomes easier when the company is strong. Not perfect. Just obviously strong. When users want it, growth is real, and the product has a sharp edge, recognition tends to happen naturally.

AI is great at pattern work.

A few months ago, I came across an interesting article that discussed how founders should take everything an investor has ever written or said, along with some other data points, and feed into ChatGPT to reverse-engineer a path to yes.

AI can summarize investor writing, cluster portfolios, surface repeated themes, and compress weeks of research into an afternoon.

Used well, AI can save you time. Used badly, it creates false confidence.

The only question to ask AI from an analysis like this is: “what does this investor seem to believe, consistently, over time?”

AI can help you see that, but it cannot replace your judgment.

The Constraint

Use pattern recognition to save time. But more importantly, use your product’s strength to earn belief.

Do enough homework to avoid obvious no’s. Write clear, honest emails that explain why you think there’s alignment. Then go back to the thing that actually matters.

Build a company that’s hard to ignore.

Fundraising isn’t a puzzle you solve once with a framework. Tools can help you waste less time along the way. But they can’t replace the part that counts: Building something that creates belief without explanation.

“Ideas, by definition, are always fragile. If they were resolved, they wouldn’t be ideas. They would be products that were ready to ship.” — Jony Ive

Ive is talking about the fragile phase. Protect it, or you’ll mistake commentary for progress.

That’s the lesson: belief first, proof next, criticism last. Flip the order and you have a performance.

The point isn’t to avoid problems. It’s to stop letting known problems replace the idea before it earns proof. In startups, that performance has a name: innovation theater.

What Innovation Theater Means.

“Innovation theater” is what happens when innovation is treated like a signal instead of a system—workshops, pilots, labs, hackathons, decks—without producing meaningful outcomes or business impact. — Steve Blank

It’s often discussed in corporate contexts because big organizations are structurally good at looking busy while staying safe.

“Pilot purgatory” is the perfect example: McKinsey found that less than 30% of IoT pilots were starting to scale, and 84% of companies were stuck in pilot mode for over a year.

But the same disease shows up inside startups, just with better taste and worse deadlines.

Proof Gets Replaced by “Being Smart.”

In early-stage startups, ideas are fragile by definition. If they were resolved, they wouldn’t be ideas. They’d be products ready to ship.

That fragility is normal. What isn’t normal is what teams do with it.

I am sure this is a scene you've lived through.

A founder walks into a Monday sync with a simple wedge: “Let’s build a one-page flow that gets users to request a quote in under 60 seconds.” By the end of the meeting, the wedge has been “upgraded” into a four-week initiative: rewrite positioning, map the journey, model pricing, define the ideal customer, and schedule user interviews “to validate.”

A few weeks later, nothing has shipped. The team has a polished narrative, a refreshed roadmap, and a new debate about whether the market is “big enough.” Meanwhile, the only thing that could have answered any of it, still doesn’t exist. All you have is less proof.

Innovation theater in a startup is when the company looks active, while output stays flat. You’re not moving forward. You’re rehearsing.

The company didn’t hit a wall. It chose a stage.

Why Theater Feels Like Progress.

Theater has three qualities founders confuse with execution.

First, it’s immediate. A meeting can happen today. A product insight might take weeks.

Second, it’s legible. A deck looks like work. A half-built prototype looks like risk.

Third, it’s socially rewarded. Objections make you sound smart. Shipping makes you vulnerable.

So the team defaults to what’s safest: the known problems, the quantifiable doubts, the performative rigor.

That’s why innovation theater is so lethal: it lets you avoid the one thing that creates truth in a startup: shipping your product.

The Props of Startup Theater.

Startup theater doesn’t look like corporate hackathons. It looks cleaner. More founder-ish. More rational.

It looks like roadmaps that keep getting “re-aligned” while the product stays the same. It looks like PRDs written to avoid blame instead of to ship a thing. It looks like pricing models debated for three sprints with zero invoices. It looks like “moat” conversations before anyone has retention. It looks like reopening the same decision every week because nothing new was learned since the last time.

The props change, but the pattern is constant: you’re optimizing for looking like you’re building instead of becoming true.

The Core Mistake: Criticism Before Proof.

There’s an order to building a startup:

Belief → Proof → Criticism.

Belief isn’t optimism. It’s a decision to treat the idea as solvable long enough to run real tests.

Proof is what you ship and what users do with it. Criticism is what you earn once there’s something real to critique.

Flip that order and you guarantee stagnation. You demand proof before belief. You litigate the idea before it exists. You turn creation into debate.

Debate doesn’t kill ideas because it’s harsh. It kills them because it’s early.

The Rule That Kills Theater.

Here’s the operating rule that strips theater out of a startup:

No critique without construction.

A few years back, I built a couple of crypro startups and in the crypto world there is one simple saying:

“Don’t trust. Validate.”

If someone challenges the idea, they owe one of three things:

1. a counter-proposal

2. a test

3. a path through the obstacle

Otherwise, it’s just performance.

“CAC will be too high” is not a contribution. “Run three acquisition tests this week with a $500 cap and measure activation” is.

“Supply won’t show up” is not a contribution. “Manually onboard 20 suppliers in 10 days and log the blockers” is.

The moment critique must cash out into an experiment, theater collapses, because experiments create accountability.

Fundraising: Where Theater Spikes.

Innovation theater gets worse the moment fundraising enters the room.

Founders start optimizing for what sounds good to investors, instead of what becomes true for users. The startup begins to perform: bigger narratives, cleaner models, sharper slides, more market sizing, more “moat.”

Meanwhile the product slows down, because shipping creates messy realities and fundraising wants tidy stories.

The irony is brutal: the most famous “fundraising stories” usually aren’t stories about decks (and don’t believe the stories tou read that start X raised Y millions with this deck — decks dont raise anything, people raise). They’re stories about founders doing whatever it took to keep shipping. Airbnb’s founders were deep in debt and sold political-themed cereal (“Obama O’s” and “Cap’n McCain’s”) to generate cash and attention, then that scrappy proof of grit became part of what got them taken seriously.

Persuasion without proof is just charisma on borrowed time.

The fastest way to raise is to stop acting like you’re raising and go generate undeniable proof.

Theater Has a Purpose, But It’s Not the Product.

Some theater is necessary. Narrative recruits talent. Narrative sells partnerships. Narrative earns attention. Narrative helps you survive long enough to ship.

But narrative is only useful when it’s in service of output.

When narrative becomes the work, the startup turns into a brand of a product that doesn’t exist yet. You don’t get momentum from that. You get exhaustion.

The rule is simple: story follows shipping. Not the other way around.

The Anti-Theater Mode.

Make every idea earn the right to be discussed by forcing it into an experiment brief: what you’re testing, who owns it, when it ships, and what behavior would count as a signal. If you can’t express an idea that way, you don’t have an idea, you have a vibe.

Run one weekly demo where only shipped work is allowed. No talk about what’s “in progress” unless it’s being shown. Nothing cleans a culture faster than a room that must face reality.

Refuse to reopen decisions unless new data exists. Not new opinions. Data. A prototype result, a user behavior change, a payment, a retention curve.

Turn criticism into construction. If someone flags a risk, their next sentence must be either a test, a workaround, or a counterproposal that can be shipped. Otherwise they’re not helping, they’re performing.

This is the startup version of “do things that don’t scale”: the unglamorous, manual, direct actions that create proof while everyone else is still debating.

Your Startup Isn’t a Debate. It’s a Lab.

The founder’s job is not to “stay positive.” It’s to protect the fragile phase long enough for it to harden into proof, without letting the startup turn into a performance of seriousness.

Innovation theater is what happens when you confuse looking like progress with making progress.

Startups don’t win by being correct in meetings. They win by shipping reality before anyone agrees it’s safe.

If you want truth, ship. If you want comfort, meet.

Over the last decade, venture capital has quietly become the default answer to building a serious company. Pitch decks, demo days, and unicorn headlines have trained founders to believe that if you’re ambitious, you raise VC. If you don’t, you’re playing small.

The default VC path is a myth. That assumption is wrong.

Not because venture capital is bad, but because it optimizes for a very specific game. One most founders never stop to question.

And the data makes that clear.

What the Data Actually Says

The real difference between bootstrapped and VC-backed outcomes isn’t hype.
It’s ownership.

And ownership loss isn’t gradual. It’s step-function.

Once venture capital enters the picture, median founder ownership compresses fast. Dilution isn’t philosophical. It’s arithmetic.

After Seed, founders collectively hold ~56% of the company.
After Series A, that drops to ~36%.
After Series B, it falls again to ~23%.
By Series D, founders typically own ~11%.

That’s before accounting for liquidation preferences, participation rights, secondary sales, or timing pressure.

This is why “big exits” often feel small to the people who built the company.

Dilution isn’t a surprise. It’s the expected outcome of the VC model. And it compounds.

Each round optimizes for speed and scale, not for preserving founder ownership. The math is predictable, repeatable, and largely unavoidable once you’re on the venture path.

This isn’t theoretical. In many successful VC-backed IPOs, founders end up with single-digit stakes. At GrubHub’s IPO, each founder held roughly 2.6%, a level of dilution that’s common after multiple venture rounds.

These are wins by market standards. They’re just very different wins for founders.

Bootstrapped companies avoid this curve entirely. They may grow slower, but ownership remains intact. When an exit happens whether at $20M, $50M, or $200M, the arithmetic works in the founder’s favor.

That’s the core distinction.

Bootstrapping Optimizes for a Different Game

Bootstrapped companies are not trying to win the same game.

They optimize for staying alive, revenue before scale, optionality, founder control, long-term cash flow, and clean exits.

They grow slower, but they don’t need permission to exist.

Research consistently shows that VC-backed firms grow faster and die faster. Bootstrapped firms grow more gradually but persist longer. They trade speed for leverage. Bootstrapped startups survive at 39% over five years. VC-backed? 16%.You're 2.4× more likely to still be standing without venture capital.

When survival is the goal, decision-making changes. You don’t chase growth that breaks the company. You don’t burn capital to satisfy timelines you didn’t choose. You build something people pay for and keep going.

Real-World Examples (Not Unicorn Lore)

This isn’t theory. It’s happened repeatedly.

Mailchimp was bootstrapped from day one. No venture capital. Profitable for years. When it sold for $12B, the founders retained meaningful ownership and control.

Basecamp has operated profitably for decades without VC, choosing autonomy over acceleration and proving that sustainability can beat spectacle.

Atlassian bootstrapped its way to a billion-dollar valuation before raising institutional capital on its own terms.

On the other side, for every celebrated unicorn, there are dozens of VC-backed companies that exit quietly at $20–60M, outcomes that look successful in press releases and disappointing on personal balance sheets.

VC Is Not Funding. It’s a Business Model.

Venture capital is not neutral money. It’s a business with its own incentives: portfolio math, power-law returns, fund lifecycles, and time-boxed exits.

In a typical $100M fund, roughly $17–20M is taken in management fees and $80–83M is actually invested. Partners get paid whether companies succeed or fail.

In the last three years, venture capital has underperformed public markets while continuing to collect full management fees, reinforcing that the model is optimized for funds, not founders.

Founders, meanwhile, optimize for control, income, longevity, personal downside, and when and whether to exit.

When those incentives align, VC can be powerful. When they don’t, tension is inevitable. Most startup “failures” aren’t the result of bad founders, but the result of mismatched optimization functions.

Liquidity = Longevity

There’s a third option founders rarely talk about: you don’t have to sell the company to relieve pressure.

Odoo is a clean example.

In late 2024, it executed a €500M transaction at a €5B valuation. One year later, it completed a ~€60M secondary at a valuation north of €7B. No IPO. No sale. Just controlled liquidity.

That matters because many founders don’t sell early because they want to. They sell early because they’re cash-poor inside a high-risk job.

On paper, they might hold €30–40M in equity. In reality, it’s illiquid, volatile, and unusable for life decisions. You can’t pay a mortgage with it. And if the company exits low or doesn’t exit at all, that paper wealth evaporates.

So founders optimize for safety. They sell too early. Not because ambition disappeared, but because pressure accumulated.

Secondaries change that equation. They let founders take pressure out of the system without killing upside. They buy patience.

That’s not “cashing out.”
It’s locking in the ability to keep building.

The Exit Market Is Quietly Changing

Something else has shifted and it’s easy to miss if you’re focused only on fundraising headlines.

In 2025, for the first time, the majority of U.S. companies going public, measured on a five-year running average, did so without venture capital.

Not fewer. Not some. Most.

Because IPOs are still the most visible, most scrutinized exits. And increasingly, the companies reaching them aren’t the ones that optimized for pitch decks and term sheets. They’re the ones that bootstrapped, raised selectively from angels, or built real revenue long before institutional capital entered the picture.

Every “pass” email.
Every partner who ghosted you.
Every fund that said “come back with more traction.”

Those rejections are no longer proof you’re on the wrong path. They may be signals that you’re on a different one.

The old playbook was simple: pitch VCs, beg for terms.
The new playbook is quieter: build, scale, choose your terms.

Traction is leverage.
Leverage lets you choose capital, rather than chase it.

Who You Actually Want on Your Cap Table

Only a small minority of investors have ever built a startup themselves. A 2022 National Bureau of Economic Research (NBER) working paper by Paul Gompers and Vladimir Mukharlyamov found that just 7% of venture capitalists founded a VC-backed company before becoming investors.

That gap matters. Founders who have carried payroll, shipped with weeks of runway, and made decisions with personal downside speak in scars, not theories.

Capital is commoditized. Experience is not.

VCs often claim they “add value,” but their own data suggests otherwise. When NBER researchers surveyed 885 venture capitalists, 50% said their returns come from deal selection. Only 25% pointed to value-add. In plain terms, most VCs believe picking the right company matters twice as much as helping operate it. That aligns with reality: the vast majority have never actually built a company. They haven’t lived the tradeoffs, the pressure, or the consequences. Expecting deep operational help from them is a category error.

The best investors tend to do three things well: write the check, open the right doors, and then stay out of the way. Smart capital doesn’t meddle. It knows when silence is the highest form of support.

If you do raise, optimize less for logos and more for alignment. Ask what they built. What broke. And what that taught them.

When Venture Capital Does Make Sense

There are cases where VC is the right tool: capital-intensive industries, winner-take-all markets, deep tech, biotech, infrastructure, and situations where speed is existential.

If delay kills the company, ownership matters less than survival.

But those cases are a subset, not the default.

Raising venture capital should be a strategic choice, not a cultural reflex.

Choosing the Right Game

Before you raise or decide not to, ask yourself:

• Do I want control or acceleration?

• Is my downside survivable?

• Am I building a company or a fund outcome?

• Would a €30–50M exit be a win for me?

You can build, scale, and exit without VCs.
They cannot exist without founders.

Choose deliberately. Understand the tradeoffs.

And if you take venture capital, do it with your eyes open because it truly fits the game you want to play.

VCs need you more than you need them.

Most founders misread traction because they ask the wrong questions. I’ve seen this happen. I’ve done it myself more than once.

A dashboard looks healthy. Signups are climbing. Engagement is “strong.” Retention looks solid enough to justify optimism. The numbers move just enough to keep hope alive.

So founders act. They extend the roadmap. They invest more time, more money, more belief.

Three months later, the numbers are flat. The roadmap didn’t unlock growth. Burn went up, but conviction didn’t.

Nothing broke. Nothing was wrong with the charts. And that’s the problem.
What failed wasn’t the data. It was the conclusion drawn from it.

Most startup dashboards are built to track activity: who showed up, how long they stayed, how often they came back. Useful signals, yes, but not decisive ones.

Activity answers the question “what happened,” not “what changed.”

They describe behavior without asking for belief. They reward curiosity without demanding a choice.

A user can browse, save, like, follow, and return for weeks without ever crossing a line that matters. Everything looks alive. Everything feels busy. But nothing irreversible has happened.

That isn’t traction. That’s rehearsal because no one has made a choice that meaningfully commits them.

Dashboards are comforting for this reason. They let founders stay busy without confronting the hardest question: is anyone willing to make a real decision here?

When Movement Feels Like Progress

This pattern showed up clearly with Inkjin.

Retention looked good. Session times were long. People came back, saved designs, explored artists. From the dashboard, it looked like momentum.

And in a sense, it was.

People were deciding. But they were finishing the journey outside the product, contacting artists directly, moving the final step to Instagram or WhatsApp, wherever friction was lowest.

This wasn’t a bug. It’s the default pattern in many marketplaces.

Inkjin was doing its job as a decision engine, helping people narrow options and build confidence. What it hadn’t yet earned was ownership of the moment of commitment.

The dashboard showed consideration at scale. What it couldn’t show was where the decision actually closed. Off-platform completion isn’t failure; it’s intent without capture.

Consideration without commitment isn’t progress. It’s exposure.

What made this impossible to ignore was what we heard from our artists. When we started gathering data on who contacted them and who actually got tattooed, a clear pattern emerged. Based on artist feedback, we estimate ~20–30 monthly bookings that originate from Inkjin discovery and close off-platform. The decisions were happening just not where we were measuring them.

That’s where we changed our posture.

Instead of treating activity as proof, we treated it as a prompt to look deeper. We stripped the dashboard down — fewer numbers, less comfort. We stopped asking how many users were active and started asking who crossed a meaningful line: who focused on one artist, who followed up after silence.

We didn’t chase growth or add funnels. We changed what we were willing to count.

That didn’t suddenly pull every decision inside the product. But it removed the illusion that we already had and that mattered more than any single metric.

The dashboard didn’t lie. It just stopped short of the moment that mattered.

As we prepare to launch booking and payments, the goal isn’t to stop off-platform behavior. It’s to make the in-app path the default: faster to book, clearer to coordinate, safer for both sides. Availability, confirmation, deposits, and simple policies aren’t features. They’re what earns ownership of the commitment moment.

Borrowed Momentum Doesn’t Compound

Most early “traction” works this way. It’s borrowed.

Borrowed from novelty. Borrowed from distribution tactics. Borrowed from the founder personally dragging users through friction.

It exists only while you’re pushing it. The moment attention shifts or effort is removed, it collapses. It doesn’t compound. It decays.

Borrowed momentum delays the truth. It doesn’t change it.

When that decay sets in, the explanations arrive quickly.

“We had users, but they didn’t convert.”
“We just needed more time.”
“The product was early.”

These aren’t diagnoses. They’re defenses. They arrive after the damage is done, when the runway is shorter and the options are worse. They explain the past without changing the future.

What Real Traction Actually Does

What founders miss is that real traction behaves very differently.

Users complain when the product breaks. They ask for features that unblock them. They work around flaws instead of leaving. They follow up when they don’t get a response. They wait through friction because leaving would be more costly than staying.

Real traction creates resistance. It isn’t when users like you; it’s when they can’t move forward without you.

They don’t just use the product. They depend on it.
They notice when something is missing and get annoyed when you change things. They would be genuinely inconvenienced if the product disappeared.

That inconvenience is the signal.

Real traction doesn’t show up when things go well. It shows up when they don’t and people stay anyway.

A Test That Doesn’t Lie

If you want something practical, do this.

Look at the last 30 days and answer three questions without guessing:

• Who proceeded with purchase intent?

• Who returned to the same decision twice?

• Who couldn’t move forward without this?

If you can’t answer them clearly, that’s the signal. You’re not measuring traction, you’re measuring activity.

I run this test on our own product, and it makes me uncomfortable every time.

The Cost of Confusing the Two

When founders confuse movement for traction, they commit too early. They hire before demand is proven. They build before pull is visible. They spend before reality has pushed back.

Each choice quietly narrows the path forward. Each one assumes the future will justify the present.

When that assumption breaks, leverage disappears and optionality goes with it. What follows isn’t learning, it’s explanation.

The data didn’t lie. It just answered the wrong question.

Traction shows up in constraint when users reorganize their behavior around the product, when decisions stop being optional, when the next step feels obvious instead of open-ended.

Until that happens, what looks like progress is just motion.
And motion, unchecked, is how founders convince themselves they’re closer than they are.

On the last day of 2025, from AI Ready CMO dropped a report into my LinkedIn inbox. Not prediction or hype. A hard look at what actually happened when AI hit marketing at scale.

Everyone adopted it. Almost nobody turned it into real advantage.
That gap is the story.

In 2025, AI stopped being a startup advantage and became table stakes. Almost everyone used it. Very few extracted value from it.

According to industry research, 88% of organizations now use AI regularly, yet only 39% can point to material business impact.

Production became infinite. Outcomes did not. For startups, this is clarifying in a way that hurts: AI doesn’t fix weak strategy. It exposes it.

Speed used to be leverage. Now it’s just noise.

AI collapsed the cost of execution. Content, ads, emails, analysis became cheap, fast, abundant. But startups don’t fail because they move too slowly. They fail because they build the wrong thing, tell the wrong story, or chase the wrong signal. AI accelerates all three mistakes.

When everyone can move faster, speed stops differentiating. Judgment becomes the bottleneck.

This isn’t a marketing problem. It’s a founder problem.
AI didn’t just flatten channels. It flattened excuses.
If you don’t know what you stand for, AI will happily generate a thousand versions of nothing.

What Actually Goes Up — And What Collapses

When execution becomes free, the market reprices everything.

The value of taste explodes. Not because creating is harder, but because filtering is. Infinite content flips the equation. Knowing what to ignore beats knowing what to make. Curation compounds. Noise scales to zero.

The value of un-Googleable expertise goes up. If the answer exists online, AI already knows it. The premium shifts to judgment built through lived experience, things learned through failure, repetition, and scar tissue. Knowledge that lives in someone’s head, not in a prompt.

The value of anti-fragile business models rises fast. When capital tightens, stories don’t save you. Cash flow does. Profitability survives. Valuation-chasing dies. AI doesn’t change that. It accelerates the reckoning.

And the value of hype-only launches collapses. Launches without substance now die in 48 hours. AI makes pattern-matched marketing obvious. The market has seen the template. It scrolls past.

AI doesn’t punish bad ideas. Markets always did.
What AI punishes is founders who confuse motion with direction.

The Taste Gap Is the Real Battleground

A defining concept of the AI era is the taste gap, the distance between what AI can produce and what humans actually value. AI is statistically average by design. It generates what is most likely, not what is meaningful.

In a market flooded with competent output, differentiation comes from editorial judgment. What to say. What not to say. What to repeat. What to kill.

In a world where everyone can publish instantly, the rare skill is deleting ninety-nine things and standing behind one.

For startups, this is existential. Early brands don’t win on volume. They win on clarity and resonance. If your positioning isn’t sharp, AI won’t save you. It will amplify your mediocrity at scale.

Creation Is Abundant. Judgment Isn’t.

Content production is no longer scarce. Attention is.

AI made it trivial to publish at scale. What it didn’t make trivial is knowing what’s worth publishing. When everyone can create endlessly, the advantage shifts from output to selection.

This is why you can’t rely on AI copy alone.

The chart below tells the story. Research comparing AI-only content with human-assisted content makes one thing clear: human + AI consistently beats AI alone. Half of the articles written entirely by AI. The other half were AI-assisted, with a human shaping the output.

The results weren’t even close.

Across originality, readability, engagement, SEO, and tone of voice, human-assisted content consistently outperformed AI-only output. Not because it was optimized harder, but because someone took responsibility and made a choice, instead of just relying on what AI spit out.

AI is here to stay. But without a human in the loop, it produces content that looks finished and performs hollow.

The problem isn’t that AI writes badly. It’s that it writes without consequence.

Authenticity Is Now Infrastructure

Social platforms didn’t just get noisier. They got synthetic. Users noticed. Trust dropped. Platforms responded by prioritizing signals of real human interaction.

Most users still engage with AI-personalized content. But platforms increasingly reward human-created material that demonstrates real connection. Authenticity infrastructure is now the dividing line between market leaders and volume optimizers.

For startups, this kills the fantasy that growth hacks are enough. People trust human or human-AI co-created content far more than fully automated output. Brands that hide their AI usage pay for it in credibility.

Authenticity is no longer a vibe. It’s a system. Founder voice. Real conversations. User-generated signals you don’t fully control. Clear disclosure about where AI is used.

That’s harder than automating posts. That’s why it works.

Discovery Has Shifted

Search is no longer about links. It’s about being cited by language models.

AI summaries, zero-click results, and conversational search mean a startup can be invisible even if its SEO dashboard looks healthy. If AI systems don’t recognize you as a credible source, you don’t exist.

By late 2025, ChatGPT hit 800 million weekly active users. Perplexity processes hundreds of millions of queries monthly. Google’s global share dipped for the first time in years. A meaningful share of users now ask AI before they ask Google.

This flips the early-stage playbook. Authority matters more than traffic. Clarity matters more than keywords. Structured knowledge matters more than content volume.

The startups that win won’t “do SEO.” They’ll become reference points.

Tools Don’t Matter. Architecture Does.

Most teams don’t build AI systems. They stack tools: One prompt tool for content. Another for ads. A third for analytics. None of them talk to each other. No shared data. No shared logic. No owner.

That’s the gap.

Teams with real leverage do the opposite. They start with clean data. They define how signals move through the company. They decide where humans intervene and where machines don’t. AI executes inside a defined system.

For startups, this is the advantage hiding in plain sight. You don’t win by adding tools. You win by designing a loop: signal → decision → action → feedback. One source of truth. One place where judgment lives.

AI compounds whatever structure you give it.

Human-in-the-Loop Is Not a Compromise

AI agents now handle most routine customer interactions better than humans. They’re faster, cheaper, and more consistent. But the empathy ceiling is real. When things matter emotionally, people want people.

Startups that automate everything look efficient right up until they look careless.

The winning model is simple:
AI handles the predictable. Humans handle the meaningful.

That balance scales trust without burning culture.

Team Shape Is Strategy

Traditional marketing organizations collapse under AI speed. Approval chains become liabilities. Generalists without depth disappear.

What replaces them isn’t unicorns. It’s translators.

People with deep expertise in one domain, systems, data, creative, brand, who can speak intelligently to the others. Execution can be separated. Comprehension cannot.

For founders, this is personal. If you can’t bridge product and narrative, no tool will do it for you.

The Real Lesson for Startups

AI didn’t replace marketers. It removed the hiding places.

It stripped away busywork and exposed what actually creates leverage: judgment, taste, trust, and systems thinking. Startups that use AI to sharpen clear thinking will widen the gap. Those that use it as a shortcut will compound the wrong kind of speed.

A few uncomfortable takeaways:

• Knowing what to ignore beats knowing what to make.

• If the answer is Googleable, AI already knows it.

• If AI is your edge, you don’t have one.

When execution is free, judgment is the only edge left. And judgment isn’t evenly distributed. Taste isn’t either.

Some teams will ship more. Others will choose better. The gap between those two grows fast. One produces volume. The other produces outcomes. AI amplifies both, but it doesn’t equalize them.

That’s why the next phase won’t reward the most automated startups. It will reward the ones willing to decide—what to build, what to ignore, what to stand behind—and punish everyone else faster than they expect.

Marc Andreessen once described startups as onions. On day one, every layer of your startup is risk. Not abstract risk. Not “execution risk.” Real, business-ending uncertainty.

That framing matters because most founders misunderstand what they’re actually building early on. A startup is not an optimization problem. It’s a navigation problem in unknown solution space. You don’t know which moves lead to success. You don’t even know what success looks like yet.

Uncertainty isn’t a side effect. It’s the product.

Startups Are Just Unanswered Questions

At the beginning, a startup is little more than a stack of unanswered questions.

Can the founders work together when things get ugly? Can anything real be built? Does the technology actually exist or is it wishful thinking? Will anyone care at launch? Is there a real market, with real buyers, at real prices? Can revenue ever exceed the cost of selling? Does growth compound or stall?

These aren’t checklist items. They’re existential risks. Until they’re answered, there is no company, only a hypothesis.

Fundraising Is a Side Effect, Not the Goal

This is where founders go wrong. They treat fundraising as progress. It isn’t.

Fundraising is a consequence of risk removal. Nothing more.

Every round exists for one reason only: to eliminate a specific set of risks. If a round doesn’t clearly do that, it wasn’t justified, no matter how impressive the headline.

Pre-Seed Is About Direction, Not Proof

Pre-seed capital exists to answer a single question: are you pointed in a direction worth pursuing?

At this stage, you’re not proving the business works. You’re proving the problem is real, the founders are aligned, and early signals justify continuing. It’s orientation, not validation.

Used well, pre-seed money makes the company less wrong. Used poorly, it creates the illusion of certainty before any exists.

Seed Capital Is for Survival, Not Scale

Seed money is not for growth. It’s for survival.

Its job is brutally simple: prove the founders can work together, prove something real can be built, prove the first launch produces signal instead of silence.

If founding team risk is unresolved, more money doesn’t help, it just delays the implosion. If product risk remains, hiring multiplies confusion rather than progress.

Series A Is About Repeatability

Series A isn’t validation theater. It’s about repeatability.

Can the product be built by a team, not just the founders? Can customers be acquired intentionally, not accidentally? Does demand exist beyond friendly early adopters?

This is where many startups fail quietly. Features ship. Headcount grows. Metrics move. But the core risks remain untouched. Motion masquerades as learning.

Later Rounds Are About Mechanics

Later rounds aren’t about vision. They’re about mechanics.

Can revenue reliably exceed cost of sale? Does growth sustain itself without brute-force spend? Can the system run without founder heroics?

At this stage, capital doesn’t create the business. It accelerates what already works or exposes what doesn’t.

Cash Is Solvent, Not Fuel

Seen clearly, cash isn’t fuel. It’s solvent.

You don’t pour it on to go faster. You apply it carefully to dissolve uncertainty, layer by layer. Used correctly, it clarifies. Used prematurely, it obscures.

When Capital Gets Ahead of Learning

The most dangerous pattern in startups is raising money ahead of risk reduction.

When capital outpaces learning, companies become brittle. Big teams amplify unproven assumptions. Speed magnifies mistakes that haven’t been validated.

The illusion is safety. The reality is fragility.

The Question Founders Rarely Ask

“How much can we raise?” is the wrong question.

The right one is simpler and harder:
Which risks must die next, and what is the minimum capital required to kill them?

That question enforces discipline. It forces sequencing. It exposes self-deception.

Dilution Is a Symptom of Unresolved Risk

Dilution isn’t usually a negotiation failure. It’s a signal.

Valuation isn’t math. It’s inverse risk. The more layers you’ve peeled away, the higher the value. Fancy models don’t change that.

If risk remains, ownership leaks.

Progress Is Certainty, Not Motion

Real progress isn’t growth. It’s certainty.

A milestone only matters if it removes a layer of risk. Everything else is noise. Busy weeks that don’t answer hard questions don’t move the company forward.

This is why some startups look slow and still win. They aren’t slow. They’re precise. By the time they raise larger rounds, much of the business is already de-risked. Capital accelerates something that already works.

A startup doesn’t die because it runs out of cash. That’s the final symptom, not the disease. It dies because unanswered questions pile up faster than answers and spending continues anyway.

Durable companies aren’t built by raising more or moving faster. They’re built by peeling the onion, one painful layer at a time.

There’s a comforting myth in startups: if you can raise money, you must be doing something right. Capital as validation. A round as proof. A valuation as evidence. It feels good because it postpones the hardest question a founder has to answer: does anyone actually want this product enough to change their behavior?

Fundraising doesn’t fix weak fundamentals. It hides them. For a while.

Money smooths the surface, sharpens the pitch, buys time, and amplifies whatever already exists underneath. If the core is strong, capital accelerates growth. If the core is rotten, capital just delays the smell.

You’ve seen this movie before.

The illusion of validation

WeWork didn’t fail because it couldn’t raise money. It raised too much, too fast, on a story that blurred the line between real estate and tech mythology. WeWork raised about $12.8 billion in funding over its history, with valuations as high as ~$47 billion at its peak. The product didn’t change. The unit economics didn’t change. The lipstick got glossier. When public markets forced the pig into daylight, reality won. Billions evaporated, not because the idea was novel, but because the fundamentals never matched the story.

Jawbone followed a quieter but equally instructive path. Nearly a billion dollars poured into beautifully designed hardware, celebrity endorsements, and prime retail placement. On the surface, everything looked right. Underneath, margins were brutal, differentiation was thin, and execution lagged. Capital didn’t solve those problems. It simply allowed them to persist longer. Jawbone didn’t collapse overnight. It faded expensively.

Clubhouse was different in tone but not in pattern. Explosive early growth, intense FOMO, and a $4 billion valuation with minimal revenue. The product was genuinely novel during lockdowns, but novelty is not a moat. Retention dropped as the world reopened and competitors copied the format. Funding validated excitement, not durability. When the excitement passed, the valuation quietly stopped mattering.

MoviePass is the cleanest example of confusing money with truth. Users loved it because it was absurdly underpriced. Investors loved the growth chart. Nobody loved the unit economics. The business model violated basic math. Capital didn’t fix the math. It subsidized it until collapse. The pig wasn’t misunderstood. It was unsustainable.

Why money lies

The pattern is always the same. Capital flows toward momentum, not truth. Growth curves, narratives, and charismatic founders are easier to evaluate than boring indicators like retention, willingness to pay, or contribution margin. So we reward what’s visible and postpone what actually matters.

The data backs this up. CB Insights has consistently shown that the top reasons startups fail are lack of market need, running out of cash, and flawed business models. Not “couldn’t raise another round.” In many cases, failed companies raised significant capital shortly before shutting down. Funding didn’t save them. It often encouraged them to keep going when they should have stopped or radically changed.

Public markets reinforce the same lesson. When went public in 2019, years of private-market enthusiasm collided with public-market scrutiny. Uber had been valued as high as $82 billion in private rounds, powered by growth narratives and future profitability promises. Once GAAP numbers mattered, the story cracked. Within months of its IPO, Uber’s stock had fallen by over 30%, wiping out tens of billions in market value. The product didn’t change. The scale didn’t disappear. What changed was the standard of truth. Public markets stopped pricing the narrative and started pricing the business. That’s the moment lipstick stops working.

What real validation looks like

What’s more interesting is what doesn’t fit this pattern.

Basecamp never chased hypergrowth narratives. It stayed opinionated, profitable, and stubbornly boring. When its founders made controversial decisions, the company didn’t collapse. Why? Because it had real customers paying for a product they relied on. No lipstick required.

Mailchimp is an even clearer case. Bootstrapped, profitable, and boring in the best way. It sold for roughly $12 billion to Intuit without ever raising venture capital. That wasn’t magic. It was validation earned the slow way, through millions of small businesses paying, staying, and relying on the product. No theatrics. No distortion.

These companies didn’t avoid fundraising because they were purists. They avoided it because paying customers gave them a different option.

The real lesson

The real lesson isn’t “don’t raise money.” It’s this: never use fundraising to answer a question it can’t answer.

Capital doesn’t tell you whether you’re right. It only tells you whether someone is willing to bet that you might be. That distinction matters more than most founders want to admit.

If you want real validation, force yourself to look where money can’t help you hide. Are people changing their behavior for this product, not just talking about it? Are they paying, not because it’s cheap or subsidized, but because it solves something painful enough? Do they come back when no one is reminding them to? Would the business still make sense if growth slowed tomorrow?

Before chasing the next round, answer a harder set of questions. What would need to be true for this company to survive without new capital for twelve months? What metric, if it moved, would actually change the trajectory of the business, not the story? What part of the product do users rely on so much that removing it would cause real anger, not mild disappointment?

Use fundraising as an accelerant, not a compass. Raise after the business tells you it works, not before. Treat capital as fuel poured on a fire that’s already burning, not lighter fluid sprayed on damp wood.

Because if the business is sound, money will make it grow faster. And if it isn’t, money will only delay the moment you’re forced to face it.

That moment always comes.

The only choice is whether you meet it early, while you still have room to change or later, after the lipstick has worn off.

And if you’re reading this heading into a new year, here’s a resolution for 2026: build something that would still make sense if the money stopped tomorrow.

Happy New Year 🍾

There’s a quiet fantasy almost every founder carries around.

It’s the idea that at some point, someone will show up and make everything better. The right investor. The right partner. The right intro. The right article that suddenly “puts you on the map.”

You don’t say it out loud, but you feel it. If I can just get this one yes, things will finally click.

Most startup stories are told that way. There’s always a turning point where someone important “discovers” the founders, writes a cheque, joins as a cofounder, or signs the big deal. From that moment on, the story is retold as if it was inevitable. Of course it worked. Look who believed in them.

Real life almost never feels like that from the inside.

From the inside, building a startup is mostly long stretches of uncertainty, tiny bits of progress, and a lot of silence from the people you wish were paying attention.

The uncomfortable truth is simple: no one is coming. And once you accept that, you can finally get to work.

The Wrong Question

The ecosystem trains us to fixate on rescue.

We’re told to chase accelerators, demo days, pitch competitions, PR, venture rounds, awards. There’s a whole industry built on selecting, judging, and anointing startups.

So you learn to orient around one question: “Will they pick me? Am I fundable?”

Will this investor fund me. Will this program pick me. Will this partner work with me. You end up treating your startup like an application, not a company.

You start obsessing over the deck, the market size, the narrative, the version of you that sounds most investable.

The stories you hear don’t help. They’re edited around highlights. “We got into Y Combinator.” “We raised from X fund.” “We were featured on TechCrunch.” Those are real milestones. But they’re not why the company exists. They’re snapshots.

I’ve been on both sides. I’ve built with funding and a big team. I’ve also built with nothing—just a laptop, a couple of people, and clients who didn’t care about my vision. They cared about one thing: whether I solved their problem.

The funded version looks better on LinkedIn. The unfunded version is where you actually learn the craft.

The Only Question

Let’s change the narrative and ask a different question.

What if no one funds you? What if no one picks you, no one rescues you with a funding round?

Would you still build this? And if yes, how?

There’s a harsh but liberating shift when you stop expecting someone or something to come and rescue you.

The job of investors is to find and fund things that are starting to work. Funding is fuel. If the engine doesn’t work, more fuel just burns faster. If your business doesn’t make sense without investor money, it probably doesn’t make sense with investor money either.

Customers are there to solve their own problems. Mentors can share insights from their experience, but you still have to draw your own map.

When you stop seeing other people’s “yes” as something you’re owed, you stop taking their “no” personally. A no is data, not a verdict.

Then the question flips from “Why won’t they back me?” to “What have I built so far that makes backing me obvious?”

That’s a better place to stand.

The Product Game

“Keep building” is not “ignore reality and grind forever.”

The product game is simple to describe and hard to play: can you solve a painful problem well enough that people keep coming back? Not in theory. Not in slides. In real life.

There’s a difference between persistence and attachment.

Persistence is running another cycle: talk to users, ship, measure, adjust.
Attachment is clinging to one version of the idea because changing it feels like admitting you were wrong.

The work is to keep building and do what you need to make progress. You keep building, but you don’t keep building the same thing in the same way just because you’re tired of being wrong.

When we started Inkjin, the idea was ambitious: to build an AI and AR tattoo platform that makes it easy for someone to go from idea to tattoo. Original designs, AR try-on, real artists, AI pricing, the full journey.

The earliest versions were not perfect, far from it. But we shipped. We put it in people’s hands. We learned from what they did, not from what we imagined.

The loop is simple and brutal: you make something, you put it in front of someone, you watch what they do, and you adapt.

If you’re doing that, you’re building. If you’re not, you’re playing startup.

The Money Game

It’s very easy to make your progress conditional.

“I’ll really push once we raise.”
“I’ll hire a proper team once we close the round.”
“I’ll fix the product after this funding cycle.”

The deeper question is survival. Can you stay alive long enough to find what works?

Money is useful. It can buy you time, talent, and margin for error. But it can also let you lie to yourself for longer.

When you don’t have money, you lose that luxury. You can’t build features nobody asked for because they’re cool. You can’t delay talking to customers for months. You have to sell something now. You have to make someone care enough to pay you.

If the only version of your working company is the version where someone else is constantly funding it, you don’t have a company yet. You have a pitch.

Don’t wait for capital to build something. Build so that capital becomes optional, and your runway becomes the speed at which you learn, adapt, and generate revenue.

One simple test: can you make €1,000 from your idea in the next 30 days? Not a million, just €1,000. If you can’t, but you believe you can raise €1,000,000 for it, something is off.

A founder who has a product, people using it, and some revenue coming in is very hard to ignore. They don’t walk into a meeting begging to be saved. They walk in deciding whether an investor can accelerate what they’ve already set in motion.

Investors are not there to create your momentum. Their job is to find heat. Your job is to create it.

So build a fire.

The Inner Game

There’s a version of entrepreneurship that looks like a never-ending roadshow — events, panels, photos, podcasts. Then there’s the real version.

You wake up at 4 a.m. wondering if you’re being irresponsible and if you’re dragging your family, your team, your health through an experiment that might not work. The anxiety doesn’t care how inspirational your last talk sounded.

You watch friends with stable jobs and feel doubt about your choices. You project certainty, while secretly rebuilding your confidence from scratch.

You’ve chosen a path where the there’s no boss to blame and no promotion cycle to wait for. Just you and the next decision.

This is why “keep building” is harder than it sounds. It means continuing to execute when the story in your head is wearing thin and nobody else is clapping yet.

That’s the job.

Build a Real Company

The most important question isn’t “am I fundable?” It’s “is this business worth building?”

Stop trying to build a “fundable” startup.

Focus on the product game until people keep coming back. Manage the money game so you don’t die before you learn. Respect the inner game so you don’t lose your sanity. Force yourself to answer the €1,000 question. Do the uncomfortable selling.

No one is coming.

Not the investor you’ve been refreshing your inbox for. Not the partner you’re sure would “change everything.” Not the mythical senior hire who will fix product, sales, and strategy in one go.

Sometimes these people appear. Sometimes they don’t.

In the movie Joker, there’s that staircase scene where Arthur stops dragging himself up the stairs and starts dancing down them. The city hasn’t changed. The system hasn’t suddenly become fair. The only thing that changes is his mindset: he stops waiting to be rescued and decides this is his story, for better or worse.

Founders face a similar moment. When you realize no one is coming to save your company, you have a choice. You can blame the world, or you can accept that it’s on you and keep building something real anyway.

Either way, your job is the same: keep building.

The moment you stop waiting and start building like it’s only on you, you become the kind of founder investors actually want to back.t

This is from a talk I gave last weekend at Techstars Startup Weekend Thessaloniki.

“Ideas are worthless. Execution is everything.” That’s startups 101. But Sam Altman says something completely different: “The good founders are the people who have ideas all the time.”

Not one brilliant idea, but thousands.

Altman isn’t talking about a single perfect concept. He’s talking about ideas on product improvements, marketing, sales, positioning, pricing, partnerships, culture. Everything, every single. day.

Yet, we obsess over the idea, afraid that someone might steal it. Billion-dollar companies aren’t built on one idea. They’re built on thousands, executed relentlessly over years. Your ideas constantly changing. Every action creates a feedback loop that shapes what comes next. Execution under uncertainty is priceless. Showing up, iterating, pivoting, and moving forward when nothing is guaranteed that’s what builds momentum.

Entrepreneurship isn’t about having the perfect idea. It isn’t about drafting a 50-page business plan or waiting for the right timing. It’s about landing in a new city, a new country, or an unfamiliar market — and figuring out how to move forward when nothing is guaranteed. The “just f***ing do it” mentality isn’t reckless. It’s a muscle, built by thinking on your feet and solving problems as they appear.

Most people overthink. They wait for certainty, for conditions to be perfect, for everything to line up before acting. Entrepreneurs don’t wait. They start, they test, they adapt, often in real time. Action isn’t blind; it’s skill. It’s assessing constraints quickly, improvising solutions, and keeping momentum when others are still hesitating.

When we first launched Inkjin in Greece last year, we had an idea: an AI + AR tattoo platform. There was no blueprint, and nothing felt certain. We hadn’t raised any funding (we still haven’t), and artists were hesitant, skeptical, or too busy to engage. Onboarding 110 professional artists while managing thousands of original designs wasn’t a process anyone had documented. Every artist had unique needs, and we had to iterate constantly to make sure the system worked for them. It was trial, error, and adjustment, over and over. Processes failed. Partners disappeared. Every day felt like firefighting. Most people would have given up. We didn’t. But it was exhausting, chaotic, and full of mistakes, often repeated mistakes. Progress was slow, uneven, and grueling.

Entrepreneurship is more than just doing. It’s learning while doing. You develop instincts no textbook can teach. You notice patterns, anticipate friction, and figure out what will work and what won’t. You learn to turn constraints into solutions, tolerate ambiguity, and prioritize action over perfection. Ideas are cheap; execution under uncertainty is invaluable.

Every day brought a new problem: a feature that wouldn’t integrate, a partner who missed a deadline, a critical bug on launch day. Every obstacle forced a decision. Do we wait for the perfect fix, or do we ship, learn, and iterate? Every time we chose action, we strengthened a muscle that no plan, no mentor, no guidebook could give us. Execution under pressure becomes instinctive. It sharpens judgment. It builds a confidence that comes from knowing you can move forward even when nothing is guaranteed.

Back at Anemone, I handled everything from ad tech to media buying and building websites, while training a junior account manager. Every project forced me to solve problems immediately, and teaching others became part of executing under uncertainty. That experience stayed with me in every startup I worked on since, leading teams, iterating processes, and building systems while learning on the go.

The “just f***ing do it” mentality often looks reckless to outsiders because it doesn’t wait for permission, resources, or guarantees. But it’s not chaos. It’s competence disguised as courage. It’s the ability to chart a course where none exists and make progress where most would see only obstacles. Every time we faced uncertainty, testing a new feature, reaching out to an artist who didn’t respond, we strengthened that muscle. We learned that constraints aren’t walls; they’re the raw material of solutions.

Launching AI + AR features like AR tattoo try-on, AI Price Estimator, and lightweight studio management (OIS) required constant adaptation. Bugs appeared, feedback was unpredictable, and features often didn’t integrate as expected. Each technical problem became a lesson in moving fast under uncertainty, learning, and iterating while keeping momentum.

Execution is messy, exhausting, and often discouraging. You will fail. You will make mistakes. You will pivot repeatedly. And that’s where growth happens. Every misstep teaches. Every constraint sharpens judgment. Every problem solved under pressure builds instincts that separate entrepreneurs from dreamers.

The discipline of action extends beyond solving problems. It’s the ability to move when fear, fatigue, and doubt scream that you should wait. It’s about building momentum in uncertainty and sustaining it through frustration. It’s the skill that allows you to test a new market, cold-email someone who could make or break your launch, or pivot a business model without losing confidence.

So the next time someone tells you to “just f***ing do it,” don’t mistake it for recklessness. It’s not about charging in blindly. It’s cultivating the muscle to act decisively under uncertainty. It’s navigating friction, turning hesitation into action, and keeping moving when progress feels invisible. That’s the essence of entrepreneurship: not the idea, not the plan, not the pitch, but relentless, disciplined execution that turns chaos into movement.

Entrepreneurship is unpredictable, messy and exhausting. And it rewards those who act while others wait. Opportunity isn’t handed out. It’s claimed by the people who do, adapt, and persist. It’s claimed by those who have learned the real skill behind “just f***ing do it.”

Have a great month and let’s go after it relentlessly.

A recent post in “The AI-Augmented Engineer” by , described building a simple iPhone app using Claude Code, a task manager designed to help manage time blindness. What stood out wasn’t the app itself, but the idea behind it:

“I’ve built things for myself that I really wish existed but have little-to-no commercial value, and I think that rocks.”

That single line captures a quiet revolution underway. For the first time, anyone with an idea — no funding, no team, no coding skills — can build something personal in hours instead of months. The result isn’t just more apps. It’s a new kind of creation.

The End of the Old Order

For years, building an app meant chasing complexity. Teams, budgets, deadlines, gatekeepers, all for a chance to get past Apple or Google’s invisible wall. If you weren’t featured, you were forgotten.

That era is fading fast.

Today, there are roughly 8.93 million apps across the App Store and Google Play. Yet only a microscopic fraction ever reach mass adoption; the rest vanish in the noise. (BankMyCell, 2025)

The great irony of software is that it promised openness, but became a maze of permissions. Innovation was centralized. Creativity became conditional. But these walls are finally starting to crack.

From Code to Command

The line between idea and execution is dissolving.

With tools like Claude Code, Replit, and Base44, building an app is becoming as easy as writing a blog post. You describe what you want for example “an app that tracks my caffeine intake and warns me when I’ve had too much,” and the AI builds it.

The no-code and low-code market is projected to reach $187 billion by 2030, growing at over 20% annually (Kissflow, 2025).

The no-code AI segment will rise from $3.83 billion in 2023 to $24.42 billion by 2030 (Grand View Research, 2024).

The new builder doesn’t write code; they define intent. They describe outcomes, not functions. The tools handle the translation.

A student might build a budgeting app for roommates. A musician could design a setlist organizer for gigs. A local group might spin up a volunteer board overnight.

Software stops being infrastructure. It’s becoming expression.

What Being a Builder Now Means

Every revolution begins with redistribution. Think of energy, knowledge, and power. This one is going to change how we build things.

When anyone can build, the hierarchy collapses. Developers no longer guard the gates. Innovation is no longer defined by those who can code, but by those who can imagine.

TikTok made everyone a creator. Substack made everyone a publisher. Platforms like Claude Code will make everyone a builder.

The new builders are not engineers of software, but architects of intent that understand what to build, why, and for whom.

By 2028, over one billion people are expected to use AI-assisted builder tools. (Datareportal, 2025).

But the real revolution isn’t just how apps are built, it’s about how they spread.

Social Is the New Distribution

App discovery used to be dictated by algorithms. Now it flows through people.

While search still matters, people no longer find apps through it alone. They find them through each other. Referrals and web links already account for roughly 20% of all App Store installs (Sensor Tower, 2021).

Discovery is leaving the store and entering the chat.

Picture this: a friend drops a link in your group chat. You tap, and it opens instantly, no downloads, no updates, no friction. Apps will spread like content, shared, reposted, and passed along in communities. Distribution becomes social, not centralized.

Apps spread like ideas now, not products. They move through trust, reputation, and shared context.

The Rise of Micro-Apps

The next generation of apps won’t chase millions. They’ll serve small communities, circles, niches. Tiny, specific tools solving problems big tech ignores: a tattoo artist’s booking system, a parent’s homework tracker, a micro-CRM for a three-person team.

It’s a return to the early web: small, scrappy, personal, but with the builder velocity of AI.

The average smartphone user has about 80 apps installed, but uses only 9 daily and 30 monthly (BuildFire, 2024).

Communities will form around needs, not markets. Each will shape its own tools, evolve them, and share them. Software will fork and adapt like open-source conversations.

The future of software isn’t scale, it’s relevance. The smaller the circle, the stronger the connection.

The Beautiful Irony

When everyone can build, software will become the language we already speak every day.

The more automated creation becomes, the more human it must feel.

Machines can generate features, test variations, and predict outcomes. But they can’t sense delight. They can’t feel wonder. They can’t tell when something crosses from useful to meaningful.

That’s still our work.

AI may accelerate creativity, but it can’t replace the pulse that gives it direction — us.

The Future Is Personal

This isn’t the death of the app. It’s the death of the gate.

Technology is circling back to its original purpose — not control, but empowerment. Software is becoming smaller, faster, more human and built by those who will actually use it.

The best ideas won’t come from corporations guessing at scale. They’ll come from individuals building for their communities, friends, and themselves.

In this world, knowing how to code won’t matter. Knowing how to see a problem and act will.

The next generation of software won’t live in stores, it’ll live in communities.
It’ll be built by creators, and you’ll find it in your Discord.