I've always had more ideas than I can take on. Some of them are good ideas even. With AI tools, I'm now able to generate fairly decent working things for more of them.
Ironically the value of implementing these ideas is dropping fast. A few weeks ago, I built a little search library that runs in the browser and doesn't need a server. It's styled after Elasticsearch and has most of it's term and matching query support, aggregation support, and I added ANN vector search as well (uses web GPU). Most of that was just me going "let's add feature X" and boom done. I used it in some websites (also built using AI) at this point. It doesn't scale but it's great for blogs, documentation sites (https://querylight.tryformation.com/, this site documents the library), etc. It all works exactly like I imagined it would. I probably could add most of the long tail of features Elasticsearch has to this library with very little effort.
But the flip side is that the library got a rather lukewarm reception on Github. It seems people are too busy coding things themselves with AI to appreciate other people's efforts much. And fair enough, if you need a search library, you could probably generate your own. Or just let the AI pick one for you. It's not like this was hard for me or a lot of work.
The economic value of these projects is dropping rapidly. I still like doing them because I like building stuff. And I think there is as a learning curve with these tools that is important to master. Because there is a lot of work that is going to need doing still and people will pay less for it and still expect decent results that you can only get if you master the tools. The ambition level will just go up to match what is now possible. People thinking that they are going to lean back while the AI works for them are in for a surprise. I work very long days the last months.