I do work on such projects, but the main goal for me is to learn, not the end result. If the end result is important, then there it's overwhelmingly likely that someone already implemented it better than I ever would, and I should just use that implementation.

I have implemented a qoi codec or a gemini client, not because I needed to use either of those, but because I wanted to understand how image codecs or network protocols worked, from bytes to end result. In the end, I learned a bit more about how computers work, how they draw stuff on screen and communicate with each other. I don't believe I would have learned much by letting an LLM do the work for me. Nor do I believe that the LLM could have done a better job than all the existing implementations of those things.

That's definitely an issue. Mind you, the general population is not a developer. I'm a mechanical engineer. I can code, use an IDE, but I hate having to figure out tooling the way you describe, and it's not a skill I'm interested in developing. What you are describing sounds to me like someone using vim and a terminal trying to convince me to stop using CLion, because they can make anything CLion can do work with their setup. Sure, I believe it, but for my part I'm going to wait for the features to be well integrated into finely designed software, I'm not going to duct-tape this stuff together to get a workflow that still involves writing out and tweaking prompts.

It also sounds to me that the AI/LLM vendors are still in a phase where they are trying to figure what the actual workflow should look like so they let their power users do that work for them. I'm not going to do that either.

Remember when Copilot was basically a super-smart version of Intellisense? It was awesome. Sure, there was a lot of pushback and concern, mainly about licensing and ethical issues, none of which are solved with the current chatbot model. But now I also have to come up with a prompt and type it out. How is that an improvement over having the LLM use surrounding code as context and figure out how to fill in the blanks? A well integrated tool beats a bolted-on chatbot any time for me. Another example would be translation: in Firefox, I can right click any text or click the 文/A button, and I can translate the text or the whole page from basically any language to any other. The frontier LLM's solution is to prompt their chatbot to do the task, which is a downgrade. Sure, I could also ask Claude to write a poem, but when I need to translate a webpage, it doesn't help much.

I get why all major AI companies push towards this solution, because they can build a single tool and sell it to everyone, and that training their models is very expensive and they can't afford to alienate any part of the potential market. But ultimately they're building Swiss army knives, which are able to do basically anything, but will never be able to allow users to tighten a screw better than a well designed screwdriver. Sure, I won't ever be able to clip my nails with a screwdriver, but if my business is tightening screws, I won't tolerate using a Swiss army knife for long.

Please build actual tools. Not textboxes for me to try and configure a non-deterministic tool. Then frustration will go down.