Why You Shouldn’t Read Startup Stories

Some time ago, after failing with my first startup, I became infatuated with reading startup stories. I thought they were cool and useful, and that I’d learn a lot from them that would help me move forward and launch another one.

My co-founder, Felicia-Daniela Moraru , and I launched Founders Project and started reaching out to founders we admired, asking them to share their stories—successes, failures, exits. The goal was to build a library of insights that any founder, anywhere, in any industry or stage, could learn from. I thought this would be valuable. We figured that if someone had built a resource like this when we were starting out, we might have avoided some mistakes and made better choices.

The project started taking off, and traffic kept growing. But that’s when I realized those stories were doing more harm than good, and we needed to shut the project down. The stories themselves weren’t the problem. The real issue was how we positioned the whole thing—what we were offering wasn’t helping founders; it was misleading them. We thought we were being helpful, but we were fooling ourselves.

The whole project was an unintentional fraud. Here’s why.

Paul Graham & the Lesson to Unlearn (a.k.a. How to Fool Yourself with a Good Narrative)

Everybody loves success and failure stories. Maybe that’s just human nature; we are drawn to narratives. But founders are particularly attracted to the success stories of other founders, and there are countless newsletters, youtube channels, and blogs that provide this type of content.

I didn’t fully grasp why success stories are so sexy until I reread Paul Graham’s essay, “The Lesson to Unlearn.” He talked about how young founders would come to him, making everything more complicated than it needed to be. They’d ask for tricks — how to raise money, how to make VCs want to invest, how to get users.

The problem wasn’t the questions. It was that they thought there were tricks, like experienced founders had some secret playbook. Today’s version might be launching on Product Hunt on Sunday because that’s when the traffic is highest.

What Graham realized was that founders complicate things for a simple reason: we’re trained that way. School teaches us to ace tests, to find shortcuts, to game the system. So when we face real-world challenges, our first instinct is to look for hacks, as if there’s some secret shortcut to success.

That’s why we look at successful founders and imagine there’s a clear path behind their achievements. Our minds can’t just accept random events; we have to string them together into a story. We want things to make sense. We want to believe that if we just follow the right steps, we’ll get the same results.

This need for order makes people believe there’s a formula for startup success. But humans have a bad habit of overinterpreting, and we tend to see patterns where there aren’t any.

The Myth of the Blueprint

People love reading about founders like Elon Musk because it’s easy to believe that with enough grit and vision, you can do what he did. But what gets lost in the process of fabricating a narrative is how much of his success came down to things he couldn’t control — timing, market shifts, even luck (he narrowly avoided bankruptcy several times).

We like to think the world makes more sense than it does. We crave stories and patterns to explain success, but this gives us a false confidence about what’s possible.

As we already know, the human mind tends to believe that the world is more explainable and predictable than it actually is. This cognitive bias leads us to come up with stories and seek patterns that seem to make sense of past events, even when those events may be purely random.

Treating these stories as blueprints ignores this truth, creating the illusion that successful founders have merely discovered a hidden formula.

This myth of the blueprint, however, is highly sellable. Look how many NYT bestsellers simply list the habits of successful people and forge a narrative uniting all of them. The narrative is entirely fabricated and often conflates a particular thing with success. If this bullet print approach were to work, eventually, reading books on the habits of successful people and replicating the habits would eventually converge with actually becoming a successful human. Instead, what usually happens is people end up with Atomic Myths — they follow steps that sound logical but were never the real reasons behind anyone’s success.

The fact that a person can tell a story in a coherent manner does not make it less random. But it makes it more interesting and attractive, as long as random life events are organized in a clear narrative that points out to the cause and to the effect, as well as to the link between them. Even if there is no causality.

You cannot just take the success stories and treat them as a recipe. The problem is that you cannot see the hidden base rate of failure that comes with similar attempts. The set of failed startups will be full of people with the exact same traits as the people who are very successful.

The Y Combinator Multiverse

Success stories often present two narratives: one focused on skill and hard work, and the other on luck. When it comes to extreme success, both are true.

I want to illustrate this through a thought experiment.

Imagine a Y Combinator multiverse. In each universe, a new Y Combinator batch starts with 1,000 startups. They all get the same seed money, the same advice, and the same network. The only difference is the skill of their founders. Now, watch what happens as these startups play out over the next few decades.

You’d expect that, on average, the more skilled founders do better. And that’s true. But if you look at the richest startup in the entire multiverse, the odds that it’s run by the most skilled founder are pretty low. More likely, that startup belongs to someone who’s talented, sure, but also got lucky — a surprise market shift, a viral moment, or a timely acquisition offer.

People often look at the top startup in their batch and think, “If I just do what they did, I’ll get the same result.” But they’re wrong. The most skilled founder is probably somewhere among the startups that did really well but didn’t take the number-one spot.

Let’s be clear: I’m not saying, “Ignore the most successful startup” or “Copy the second-best.” I’m saying you should think critically about which paths you follow. Ask yourself, how likely is it that the same strategy will work again? If there were ten different Y Combinator cohorts, how often does that number-one startup come out on top again? And how often does it struggle or even go bust? Are you okay with not just their success but also the possibility of their failure?

To get to the top, you often have to make choices that lower your average outcome. So, do you really want to aim for the highest possible score? It might come with hidden costs — not just effort, but risk, the kind that boosts your best-case scenario but drags down your average results.

Let’s use a different example to make this clearer.

Imagine ten parallel universes, each with the same 100 startups in a Y Combinator batch. They all have the same ideas, the same markets, and the same starting capital. Half the founders decide to swing for the fences — they go for aggressive growth, make big pivots, or burn through cash to get earn a press release and a backlink on a well-known website.

The other half plays it safer. They focus on solid growth, conserving cash, and finding product-market fit before they scale.

In every one of these universes, the top-performing startup is almost always from the risk-takers. But — and here’s the funny part — it’s a different startup each time. The founder that wins in one universe might be scraping by in another. Why? Because luck matters. A lot. The startups that took big risks had huge wins when things went their way, and they crashed hard when they didn’t.

Meanwhile, the cautious founders — those who made steady decisions — did well in nearly every universe. They didn’t end up with the absolute highest results, but they consistently did well. If you don’t take extreme risks, even if you’re the most skilled founder, you’ll likely be outperformed by those who do. But if you do take those risks, your average outcome will often be worse than if you’d been more conservative.

Now, a few clarifications. First, I’m not saying you shouldn’t take risks. Here, we’re talking about extreme risks — the kind that can sink your startup if they don’t work out. Taking small, calculated risks is usually smart. Think of it this way: distinguish between risks that you can recover from and those that might knock you out completely. Aim for the first type, not the second.

Second, this doesn’t mean you shouldn’t aim high. It means that, when choosing your approach, you should be mindful of survivorship bias. Don’t just pick strategies that look good because they worked once. Look for ones that give you a solid chance of success across different scenarios.

Survivorship Bias and Extreme Risks

During World War II, researchers at the Center for Naval Analyses studied the damage on bombers that returned from missions. They saw bullet holes clustered in certain areas and figured, logically, that those spots should get extra armor to reduce losses.

But Abraham Wald had a different take.

Wald, a Hungarian mathematician with the Statistical Research Group, pointed out a flaw in their thinking: they were only looking at the planes that made it back. The ones that didn’t return weren’t part of the data.

What he realized was that the bullet holes in the returning planes showed where a plane could get hit and still survive. The parts that didn’t have bullet holes were actually the weak spots — because hits in those areas likely caused the planes to go down.

So Wald suggested reinforcing those unscathed areas instead. It was a classic case of avoiding survivorship bias: seeing the full picture by considering what’s missing, not just what’s in front of you.

Unfortunately, survivorship bias is endemic to startup culture. We see those who have survived and mistakenly assume they represent the entire set of possibilities. It’s a natural part of how we think — we pay attention to the winners and ignore the losers.

Survivorship bias skews our perception of what it takes to succeed. When you hear about a startup that made it big, it’s tempting to believe that if you just follow their strategy, you’ll get the same result. But you’re not seeing the hundreds of other founders who tried similar strategies and failed. The survivors seem like they hold the secret to success, but they might just have been the lucky ones who avoided disaster.

For every Musk or Bezos, there are thousands of other founders who tried similar strategies and failed. You don’t hear about those because they didn’t become billionaires. The strategies that made these high-profile founders successful may have worked in their specific circumstances, but those circumstances are almost impossible to reproduce. The expected outcome of a risky strategy is always lower than what appears from the sample of winners.

They might have had a general sense of what worked, but they were also lucky in ways they couldn’t foresee. Maybe they launched their product at the perfect moment when the market was ready. Maybe a random early hire turned out to be a perfect fit. Or maybe a key competitor made a mistake that cleared the way for them. It’s easy to rationalize these events after the fact, but nobody can truly plan for them.

Some founders take huge risks — launching too early, burning through cash, pivoting wildly — and if they survive, they look like visionaries. But we forget that many others who did the same things didn’t make it. Their stories don’t get told because they’re no longer around to tell them. Surviving doesn’t necessarily mean that their approach was optimal or even a good idea. It just means they got through without hitting a wall, this time.

The mistake is thinking that the survivors are the rule, not the exception. This makes startup culture an echo chamber of risky advice. We read stories about how a founder made a last-minute pivot that turned everything around, or how they bet everything on one huge deal, and we assume that’s a replicable path.

But those stories are the outliers. For every success story, there are dozens of failures that looked almost identical until the moment things went wrong.

Focus on Surviving Long Enough to Learn Before Scaling Over the “Hack”

The most important thing for a startup is simply staying alive long enough to learn what actually works. It’s tempting to focus on finding the “secret” to success — a hack that will get you millions of users overnight. It might give you a temporary boost, but if your underlying product or business model isn’t sound, that boost won’t last.

Instead, a founder’s real focus should be on understanding the broader principles of risk and resilience. Early on, it’s better to optimize for survival rather than rapid scaling. Every startup faces unknowns, and the longer you survive, the more time you have to learn, iterate, and adapt to the market. Surviving is underrated because it doesn’t make headlines. But it’s through surviving that you build a product people actually need and develop the knowledge that can eventually lead to real, lasting growth.

Evaluate Risks You Can Recover From Versus Those That Could Cause Irreparable Damage

When founders think about risk, they often get it wrong. The key to managing risk isn’t to avoid it completely — it’s to take risks that won’t destroy you if things go wrong. Think of it like a game: there are some moves you can make that might set you back a bit but still leave you in the game. Other moves, though, could knock you out completely if they don’t work out.

You should take risks that you can afford to lose, because that’s where you learn the most. But avoid risks that could cause irreparable damage, like burning through all your cash to bet on a feature that might not even attract new users.

The sweet spot is finding risks that have high potential upside but won’t ruin you if they fail. That’s where you want to live as a founder — not going all-in on a single roll of the dice, but taking bets that give you a chance to come back stronger if they don’t work out.

Looking Beyond the Headlines

One of the biggest mistakes founders make is taking startup stories at face value. The stories that get shared — especially the dramatic success stories — are often the least helpful. They tend to be overly simplified, focusing on the big, flashy moments like “the pivot that saved the company” or “the viral launch that blew up.” But those moments aren’t the whole story, and they’re almost never the part that you can replicate.

If you want to learn from startup stories, you have to go deeper. Don’t just ask, “What did this founder do?” Ask instead, “Why did this work in their particular situation?” Look for the underlying principles — like how they adapted to their users’ feedback, or how they identified a key problem in their market.

Understand which elements of a founder’s journey are universally applicable, like listening closely to customers, and which are context-specific, like launching at the perfect moment or stumbling into a market shift.

Learning to separate these out will give you a more realistic sense of what might work for your own startup.

Final Takeaway: Learning from the “Almost-Winners”

We have a tendency to obsess over the absolute top winners, but they’re not always the best teachers. There’s often more value in learning from the founders who made it to solid, steady success — those who were successful but not necessarily the ones writing billion-dollar acquisition stories.

If there’s one takeaway I want you to remember from this article, it’s this one — if you are in the 50th percentile as a startup, you will end up in the top 1% in 15 years. Being average for the long term makes you above average over time.

These founders might not be at the top of the TechCrunch headlines, but they’ve figured out how to build a business that sustains itself, how to make customers happy, and how to avoid the pitfalls that lead to failure.

These “almost-winners” often have a more grounded perspective because they’ve seen what happens when a startup takes risks it can’t handle. They’re also the ones who’ve focused on things like slow but consistent growth, maintaining a good culture, or developing strong customer relationships.

Their stories might not sound as exciting, but they’re often more practical. In many ways, they’ve figured out how to play the long game, and that’s the kind of wisdom that’s more useful than a quick path to the top.