BUSINESS
I’ve watched a lot of AI startups over the last three years. The ones that fail rarely fail because the AI doesn’t work.
The technology, by and large, is the easy part. You can build something genuinely impressive with the APIs and open-source models available today. The hard parts are the same hard parts that have always killed startups: distribution, unit economics, and the painful gap between what people say they’ll pay for and what they actually will.
The Demo Trap
AI products are uniquely dangerous in this respect because they demo beautifully. A well-constructed demo of an AI tool can produce a room full of people who genuinely believe they’re looking at the future. Investors. Enterprise buyers. Journalists. The demo works. The problem is that between “works in a demo” and “works reliably in production at scale” lies a chasm that has swallowed many well-funded teams.
“Between ‘works in a demo’ and ‘works reliably in production at scale’ lies a chasm that has swallowed many well-funded teams.”
The Wrapper Problem
A significant cohort of AI startups are, essentially, thin wrappers around foundation models. The user experience might be genuinely nice. The workflow integration might be thoughtful. But the core capability comes from a model built by someone else, and there is very little stopping that model provider from building the same feature themselves.
OpenAI, Anthropic, and Google have all done exactly this — absorbed use cases that startups had built into their core product. The startups that survive are the ones that have built something the foundation model providers can’t easily replicate: deep domain expertise, proprietary training data, regulatory relationships, or switching costs that accumulate over time.
What Actually Works
The AI companies I’ve seen build durable businesses share a common pattern: they started with a very specific, painful problem in a domain they understood deeply, they built for retention rather than viral growth, and they treated AI as an ingredient rather than a product. The AI isn’t the pitch. The outcome is the pitch.
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