I don't know how ya'all are letting the AIs run off with these long tasks at all.

The couple times I even tried that, the AI produced something that looked OK at first and kinda sorta ran but it quickly became a spaghetti I didn't understand. You have to keep such a short leash on it and carefully review every single line of code and understand thoroughly everything that it did. Why would I want to let that run for hours and then spend hours more debugging it or cleaning it up?

I use AI for small tasks or to finish my half-written code, or to translate code from one language to another, or to brainstorm different ways of approaching a problem when I have some idea but feel there's something better way to do it.

Or I let it take a crack when I have some concrete failing test or build, feeding that into an LLM loop is one of my favorite things because it can just keep trying until it passes and even if it comes up with something suboptimal you at least have something that compiles that you can just tidy up a bit.

Sometimes I'll have two sessions going but they're like 5-10 minute tasks. Long enough that I don't want to twiddle my thumbs for that long but small enough that I can rein it in.

I find it interesting you're all writing 'the AI' as if it's a singular thing. There's a myriad of ways to code with a myriad of AI's and none of them are identical. I use a Qwen 3 32B with Cline in VSCode for work, since I can't use cloud based AI. For personal projects, I use Codex in the cloud. I can let Codex perform some pretty complicated tasks and get something usable. I can ask Qwen something basic and it ends up in a loop, delivering nothing useful.

Then there's the different tasks people might ask from it. Building a fully novel idea vs. CRUD for a family planner might have different outcomes.

It would be useful if we could have more specific discussions here, where we specify the tools and the tasks it either does or does not work for.