[majora2007]

I think LLMs provide value, used it this morning to fix a bug in my PDF Metadata parser without having to get too deep into the PDF spec.

But most of the time, I find that the outputs are nowhere near the effect of just doing it myself. I tried Codex Code the other day to write some unit tests. I had a few setup and wanted to use it (because mocking the data is a pain).

It took about 8 attempts, I had to manually fix code, it couldn't understand that some entities were obsolete (despite being marked and the original service not using them). Overall, was extremely disappointed.

I still don't think LLMs are capable of replacing developers, but they are great at exposing knowledge in fields you might not know and help guide you to a solution, like Stack Overflow used to do (without the snark).

[ojosilva]

I think LLMs have what it takes at this point in time, but it's the coding agent (combined with the model) that make the magic happen. Coding agents can implement copy-pasting, it's a matter of building the right tool for it, then iterating with given models/providers, etc. And that's true for everything else that LLMs lack today. Shortcomings can be remediated with good memory and context engineering, safety-oriented instructions, endless verification and good overall coding agent architecture. Also having a model that can respond fast, have a large context window and maintain attention to instructions is also essential for a good overall experience.

And the human prompting, of course. It takes good sw engineering skills, particularly knowing how to instruct other devs in getting the work done, setting up good AGENTS.md (CLAUDE.md, etc) with codebase instructions, best practices, etc etc.

So it's not an "AI/LLMs are capable of replacing developers"... that's getting old fast. It's more like, paraphrasing the wise "it's not what your LLM can do for you, but what can you do for your LLM"