Comment by nerptastic

I’m a newer full stack engineer, previously did mostly web dev. It’s been useful in the areas that I’m not super interested in. We’re working on a 700KLOC legacy monolithic CRUD app with 0 documentation, it’s essentially the Wild West. We’ve found it very difficult to apply AI in a meaningful way (not just code output, reviews, documentation writing, automation). For a small team with lots to do on what is essentially a “keep the lights on” we’re in an interesting place, as it feels the infrastructure / codebase isn’t set up to handle newer tools.

I use the code generation heavily in my day to day, though verification is a priority for me, as is gaining an understanding of the business logic + improving my skills as a developer. There’s a healthy balance between deploying 100% generated code and not using the tools at all.

It’s useful for research tasks, identifying areas I’ll be working in when developing a feature. However, this team has a gigantic backlog and there are TONS of things we are behind on, so it does feel like AI isn’t moving the needle for us, though it is helpful. I’d like to apply it in different areas, but my senior engineer is very anti-AI, so he doesn’t find the tools useful and is actively against using them. Like I said, there’s surely a balance…

I see us using / relying on them more in the future, due to pressure from above, along with the general usefulness of them.