What are some recommended strategies for building a product in the generative AI market?

I think the question of differentiation is interesting, how to differentiate as someone trying to build a product in a market. All the AI founders, generative AI founders, probably get the same question from VCs like ‘hey, what's your moat?’ At the beginning, I definitely felt like this is a good question or I understood the question. But after thinking about it, I realized that there really aren't moats in SaaS a lot of the time. As someone who was building a note-taking app and there are a bunch of other note-taking apps. In productivity, there's a bunch of project management apps. Then it's like, ‘oh, wait, there's a lot of analytics apps, as well.’

There's a bunch of observability and monitoring startups. I don't know if any of them has a moat, for real, or it's just a pretty big market and it's not super winner-take-all. Why are there so many billion dollar project management companies? I don't know. What moats does SaaS have, in general? It's not really apparent. At the end of the day, execution is still everything. If you’re building the tenth customer support bot trained on docs, or the tenth startup doing writing or copywriting, which under AI, you just have to sprint, I don't know, and hope that you have the best founder-market fit, that you have the best distribution and data and brand. Those are the things that don't change as moats. 

So even for a lot of AI companies, I feel every time a new GPT gets released, a bunch of startups just die. That could happen again to all the ones being built on GPT-3.5 or 4, those could all go away by GPT-5 because the base model is just so much better. Or, actually fine-tuning and being an amazing prompt engineer doesn't really matter that much when it's just the bar constantly getting raised.