Coming at this from a design perspective, ultimately, I think it’s because we’re following and repeating the same patterns we see at larger companies or trendy startups that look interesting or useful, but when when the “end product” is repeated across domains, it’s either too broad of a solution to be useful within a specific context, or it’s too narrow to be applied to multiple contexts. AI (across the different ways we’ve defined it over time) really only enables 5 things, either individually or combined: perception, organization, inference, production, or action. If you use those enablements as starting points to ask questions about whether AI needs to be used at all in a particular context, and you can articulate WHY a system needs to sense something, and WHY it needs to act on what its sensed, then you can start to see where it can actually be useful in the context you’re building. Not everything needs to be a generator, or if it is, it doesn’t always need to be a chat interaction, etc.

I see the same, and I am getting bored. I open application listing, like BetaList, ProductHunt and I see the same. A lot of people are trying to produce something, using AI, Loveble, Base 44 or any other 'no coding tool'. The hype is too big, all the complexities are hidden behind AI, and there is nothing that catches the eye.

Like the whole market is flooded with the same thing, just with different skin

You need to find niche ideas that didn't exist because of input/output tradeoffs which still requires some engineering chops to pull off even with AI.

it's like everyone is launching their own interpretation to a problem/idea. persuading people is really hard, you know.