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.
I'm not OP but my experience with Cursor is similar. I have a B.S. in computer science from UW-Madison and have been a full-time professional software developer since 1998. This stuff is the real deal. I mostly see people not willing to put in the time to learn. There is a big learning curve here--don't let the fact that it's English trick you into thinking there's no skill involved. Your experience is actually what makes this work; greener devs will be unable to get the AI out of a rut or keep it on the straight and narrow, but an experienced dev can sprinkle in some occasional wisdom and get the machine going again. This stuff is fool's gold for "vibe coders" but rocket fuel for experienced developers using it as a tool.
I think more often you'll find it's the mediocre coders (like myself) that have trouble using AI. The software developers and CS majors just know exactly what to tell it to do and in the *exact* language it could best be understood. That's just my experience.
Also, I get caught up in multiple errors that will never go away and, since I'm stepping out of my wheelhouse with libraries or packages I'm completely unfamiliar with, I'm completely helpless but to diagnose what went wrong myself and improve upon my code prompting skills.
Don't get me wrong. AI makes possible many things for me. However, I think professional coders probably accomplish much more.
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.
Hello could you tell us what makes you use all of gemini-2.5-pro, claude-4-sonnet, and o3 for different purposes?
I'm not OP but my experience with Cursor is similar. I have a B.S. in computer science from UW-Madison and have been a full-time professional software developer since 1998. This stuff is the real deal. I mostly see people not willing to put in the time to learn. There is a big learning curve here--don't let the fact that it's English trick you into thinking there's no skill involved. Your experience is actually what makes this work; greener devs will be unable to get the AI out of a rut or keep it on the straight and narrow, but an experienced dev can sprinkle in some occasional wisdom and get the machine going again. This stuff is fool's gold for "vibe coders" but rocket fuel for experienced developers using it as a tool.
Idk, I’ve been doing this for 15 years professionally and many years before and it’s still amazing to me
I think more often you'll find it's the mediocre coders (like myself) that have trouble using AI. The software developers and CS majors just know exactly what to tell it to do and in the *exact* language it could best be understood. That's just my experience.
Also, I get caught up in multiple errors that will never go away and, since I'm stepping out of my wheelhouse with libraries or packages I'm completely unfamiliar with, I'm completely helpless but to diagnose what went wrong myself and improve upon my code prompting skills.
Don't get me wrong. AI makes possible many things for me. However, I think professional coders probably accomplish much more.
If you've mentored junior devs, talking to the AI in such a way that gives good results is pretty similar, so that may be why.
Knowing how to talk to your wife, your kids and your AI are key to a happy life :)
Senior developer, decades of experience