Generative AI coding tools and agents do not work for me

To some degree, traditional coding and AI coding are not the same thing, so it's not surprising that some people are better at one than the other. The author is basically saying that he's much better at coding than AI coding.

But it's important to realize that AI coding is itself a skill that you can develop. It's not just , pick the best tool and let it go. Managing prompts and managing context has a much higher skill ceiling than many people realize. You might prefer manual coding, but you might just be bad at AI coding and you might prefer it if you improved at it.

With that said, I'm still very skeptical of letting the AI drive the majority of the software work, despite meeting people who swear it works. I personally am currently preferring "let the AI do most of the grunt work but get good at managing it and shepherding the high level software design".

It's a tiny bit like drawing vs photography and if you look through that lens it's obvious that many drawers might not like photography.

It wont be the hippest of solutions, but you can use something like Devstral Small with a full open source setup to get experimenting with local LLMs and a bunch of tools - or just chat with it with a chat interface. I did pingponged between Devstral running as a chat interface and my regular text editor some time ago to make a toy project of a raytracer [0] (output) [1] (code).

While it wasn't the fanciest integration (nor the best of codegen), it was good enough to "get going" (the loop was to ask the LLM do something, then me do something else in the background, then fix and merge the changed it did - even though i often had to fix stuff[2], sometimes it was less of a hassle than if i had to start from scratch[3]).

It can give you a vague idea that with more dedicated tooling (i.e. something that does automatically what you'd do by hand[4]) you could do more interesting things (combining with some sort of LSP functionality to pass function bodies to the LLM would also help), though personally i'm not a fan of the "dedicated editor" that seems to be used and i think something more LSP-like (especially if it can also work with existing LSPs) would be neat.

IMO it can be useful for a bunch of boilerplate-y or boring work. The biggest issue i can see is that the context is too small to include everything (imagine, e.g., throwing the entire Blender source code in an LLM which i don't think even the largest of cloud-hosted LLMs can handle) so there needs to be some external way to store stuff dynamically but also the LLM to know that external stuff are available, look them up and store stuff if needed. Not sure how exactly that'd work though to the extent where you could -say- open up a random Blender source code file, point to a function, ask the LLM to make a modification, have it reuse any existing functions in the codebase where appropriate (without you pointing them out) and then, if needed, have the LLM also update the code where the function you modified is used (e.g. if you added/removed some argument or changed the semantics of its use).

[0] https://i.imgur.com/FevOm0o.png

[1] https://app.filen.io/#/d/e05ae468-6741-453c-a18d-e83dcc3de92...

[2] e.g. when i asked it to implement a BVH to speed up things it made something that wasn't hierarchical and actually slowed down things

[3] the code it produced for [2] was fixable to do a simple BVH

[4] i tried a larger project and wrote a script that `cat`ed and `xclip`ed a bunch of header files to pass to the LLM so it knows the available functions and each function had a single line comment about what it does - when the LLM wrote new functions it also added that comment. 99% of these oneliner comments were written by the LLM actually.