Matt Garman sees a shift in software development as AI automates coding, telling staff to enhance product-management skills to stay competitive.
The only person in my company using AI to code writes stuff with tons of memory leaks that require two experienced programmers to fix. (To be fair, I don’t think he included “don’t have memory leaks” in the prompt.)
I find that my programming speed is up 15-20 percent since I started using supermaven copilot. I also have become better at naming functions as it increases the odds of the copilot understanding what I’m trying to do.
Also writing tests go way faster.
Are you able to share what kinds of applications and what languages you write in? I’m still trying to grasp why LLM programming assistants seem popular despite the flaws I see in them, so I’m trying to understand the cases where they do work.
For example, my colleague was writing CUDA code to simulate optical physics, so it’s possible that the LLM’s failure was due in part to the niche application and a language that is unforgiving of deviations from the one correct way of writing things.
Sorry I didn’t see this earlier.
It’s very vanilla node backend stuff with popular Frameworks such as koa and nest so that makes it easier to give me good assistance I guess.
