You have a billion-dollar idea. You’re also terrified it’s actually a zero-dollar idea. So, you do what any rational founder does in 2024: you look for a shortcut to reality.
Enter the ‘Startup Graveyard.’ The premise is beautiful in its simplicity. You paste your brilliant startup idea into a box, and it spits out the corpses of similar startups, complete with autopsy reports on why they failed. It promises to be the ultimate reality check before you sink your life savings into another doomed SaaS platform.
But there’s a catch. The autopsies are fake.
Over on Hacker News, a commenter tested the tool with their own world-changing concepts. The verdict? ‘Very cool idea, however the results are hallucinated nonsense.’
A graveyard built by a hallucinating AI isn’t a warning sign; it’s a funhouse mirror.
We want to believe that failure is objective. That somewhere in a pristine database, there is a clean, factual record of why that obscure B2B fintech from 2019 died. But the harsh truth about the startup world is that failure is rarely documented accurately. Founders lie on the way out to save face. Investors spin losses into ‘learning opportunities.’ The real reasons a company goes under—internal feuds, technical debt, sheer bad timing—are almost never written down.
When an AI tries to fill in the blanks of undocumented startup deaths, it doesn’t tell you ‘I don’t know.’ It does what it always does: it hallucinates a plausible fiction. It invents a post-mortem that sounds exactly like every other TechCrunch obituary. It tells you your idea failed because of ‘poor user acquisition’ or ‘lack of product-market fit.’ It sounds incredibly smart. It is entirely made up.
We’ve built a machine that lies to us to protect us from the lies we tell ourselves.
You think you’re de-risking your next venture by learning from history. Instead, you’re absorbing AI-generated folklore. You aren’t avoiding the mistakes of the past; you’re being scared off by a ghost story invented by a language model trying to please you.
The startup graveyard is a brilliant concept. We absolutely need a way to map the minefields of tech history. But relying on a language model for your reality check is like asking a con artist for financial advice. The tool promises to save you from wasting time and money, but by trusting its hallucinated data, you’re falling victim to a second-order failure: making decisions based on a reality that never existed.
You can’t outsource survivorship bias to a language model. If you want to know why startups fail, stop asking the AI. Go talk to a founder who just lost everything. They might not tell you the whole truth, but at least their lies will be real.
FAQ
Q: Isn't it obvious that AI might hallucinate? Why trust it at all?
A: Because the design of these tools implies authority. When a UI promises to show you 'why startups failed,' the average user assumes it's querying a verified database, not generating a probabilistic guess. The interface hides the hallucination.
Q: So should founders just ignore historical failure data?
A: No, but they need to stop looking for clean, automated answers. Real failure data is messy, undocumented, and heavily biased. If you want the truth, you have to dig for primary sources, not accept an AI's summary.
Q: Is an AI-generated post-mortem really that harmful if it sounds plausible?
A: Yes. It creates a false sense of de-risking. A founder might abandon a viable idea because an AI invented a fake failure reason, or worse, ignore a real fatal flaw because the AI didn't accurately identify it in past competitors.