Comment by zackham

I'll add to the sibling comment and say I've been writing software for money for 25+ years, have a CS degree, and have found immense leverage with these tools. I put in the time on hobby projects over the past couple years to figure out how best to integrate it all into my work, and now I'm in a place where it's saving me significant amounts of time every time I produce code, and I'm getting the quality of results the project demands. I use gemini-2.5-pro, claude-4-sonnet, and o3 for different purposes, and have a variety of techniques to avoid pitfalls and get the results I'm looking for. There are a lot of ways to unsatisfactory results, but it's possible to get usable results that save time. I've shared my enthusiasm and seen other devs dabble, get poor results, and go back to their practiced methods of writing software–so I'm not surprised to see so many skeptics and naysayers. It isn't easy or obvious how to make this stuff work for you in larger codebases and for meatier problems. That doesn't mean it's impossible, and it doesn't mean it's not worth it to climb the learning curve. As the models and tools get better, it's getting a lot easier, so I suspect we'll see the number of people denying the utility of LLM-generated code to shrink. Personally, I'd rather be reaping the benefits as early as possible, because I can get more stuff done faster and more pleasantly.