Domain expertise and narrow models can definitely be an advantage but you need to be somewhat successful before you can get sufficient data to train or refine a

Domain expertise and narrow models can definitely be an advantage but you need to be somewhat successful before you can get sufficient data to train or refine a model with sufficient domain expertise to be a differentiator. You definitely do not need to train your own base model to be successful, but if your entire pipeline is a system prompt or three in a small agent graph... You didn't build a product, you built a hobby tool over the weekend no matter how much UX/UI polish you put on it. I do think this question, and many start-ups are thinking about how they want that sweet AI money and are starting their business from there rather than from a problem. If you see a problem that is labor intensive and could be done by mechanical turk... Well you're probably on to something and an AI language model can probably solve that problem. The companies and AI products I think that are going to last either aren't starting with AI they're focusing on a problem and have reasoned their way to AI OR they're doing some deep stealth research into the problem over a long period of time to be able to develop domain-specific data, techniques, and plans so they can fine-tune their own model before ever showing it to a potential customer. You better be sure you have a good plan if you're going to try and be the latter.