3 ms·
>No, the code is actually almost always correct That's not my experience, especially when the inputs are bugs or performance issues. It frequently hallucinates
by nijave 5mo ago
>No, the code is actually almost always correct
That's not my experience, especially when the inputs are bugs or performance issues. It frequently hallucinates and misdiagnosis without a guiding hand. However, it can still RCA and analyze well and improve efficiency if you keep an eye on what it's doing and push it the right direction.
> If you were to give human developers the same amount of feature/scope documentation you would also see your productivity skyrocket.
I think you run into a ceiling how fast a person can digest and analyze the info compared to a machine
- BoxedEmpathy 5mo agoWhat tools are you using? What settings? What process? What's your code review like? I think this varies a lot. I find with a c++ project I'm working on that the LLM needs a lot of guardrails and guidance, and still gets a lot wrong. But with a vite/js project it often one shots complex and intricate changes in large codebases.
- nijave 5mo agoClaude Code with Opus 4.7 xhigh effort Datadog + Python with a little AWS It does better at writing code but diagnosing bugs and performance issues is a bit of a crapshoot. It's decent at diagnosing but when tasked with improving performance it gets a bit sketchy. It'll write something that runs but often times it either has subtle functionality changes or mediocre improvements Other times I'll repeatedly have to push it to find the root cause. It'll say "hey this downstream service threw an exception that propagated as a 500" and I'll have to remind it that's a first party service with info available in the trace and source code also available that it needs to continue investigating.