I've been investigating vertical AI startups profoundly for the past few weeks. I think we're in a very strange part of the cycle in AI startup funding/development. Some thoughts (hot takes?) 1. Literally every vertical (finance, law, healthcare etc) is now populated with AI startups building on top of foundation models. If you start today, it's too late to get first-mover advantage. 2. However, foundation models are still not quite there yet to solve problems in these verticals in a tangible, bulletproof way. Those who built GPT wrappers (even if they refuse to admit the label...) rely on OpenAI's next big model to truly prove sticky long-term retention. And those who decided to train their own specialized models (like Harvey) are apparently not outperforming smart general models (GPT-4o, Claude 3.5 Sonnet). 3. Startups are facing a massive dependence on big AI labs shipping the next big model. And once that happens, it might just be that we won't need GPT-wrappers at all. ChatGPT will be enough for whatever task we hand them. 4. This is fundamentally so different from the internet and mobile innovation cycles. Back then, incumbents could not touch every single vertical with their product offerings, so startups filled in the void and became multi-billion dollar companies (e.g. Apple launched the app store, but wouldn't build apps for food delivery, dating, ride-sharing etc). Now, when GPT-5 launches, OpenAI can touch virtually every industry they want. 5. My sentiment is that we're living a kind of "born too late to explore the Earth, born too early to explore space" vibe in this 23-24 cycle in the realm of AI startups. And when the rocket ships to space are finally ready (i.e. truly smart general LLMs), vertical AI startups will capture much less value vs. incumbents when compared to previous cycles.