Opus 4.6 is nuts. Everything I throw at it works. Frontend, backend, algorithms—it does not matter. I start with a PRD, ask for a step-by-step plan, and just execute on each step at a time. Sometimes ideas are dumb, but checking and guiding step by step helps it ship working things in hours. It was also the first AI I felt, "Damn, this thing is smarter than me." The other crazy thing is that with today's tech, these…
The replies to this really make me think that some people are getting left behind the AI age. Colleges are likely already teaching how to prompt, but a lot of existing software devs just don't get it. I encourage people who aren't having success with AI to watch some youtube videos on best practices.
I'm working in a codebase of 200+ "microservices", separate repos, each deployed as multiple FaaS, CQRS-style. None of it my choice, everything precedes me, many repos I know nothing of. Little to no code re-use between them.
Any trace of "business logic" is so distributed in multiple repos, that I have no possible use of LLM codegen, unless I can somehow feed it ALL the codebase.
I've tried generating some tests, but they always miss the mark, as in the system under test is almost always the wrong one.
I guess LLM are cool for greenfield, but when the brownfield is really brown, there's no use for LLMs.