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by noelwelsh
4 hours ago
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I wish people would describe in more detail the tasks they use LLMs to code. My experience is that simple components in an existing architecture are fine, but anything requiring architectural considerations quickly becomes a mess. On my projects (e.g. a ui framework), running multiple agents in parallel would just increase the speed at which it can stuff up the project. |
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https://www.trigosec.com/insights/mob-programming-for-one/
The short version is that I don’t let AI agents work unsupervised on my code. I treat them like participants in a mob programming session instead of autonomous developers. Different agents get different roles (implementer, reviewer, architect, security reviewer, etc.), and I stay involved throughout the process.
I also agree with your point about architecture. Generating isolated components is relatively easy; preserving and evolving the architectural boundaries across a larger codebase is much harder.
We’re still missing a good way to express and measure architectural quality. Until then, architecture heavy work requires much closer supervision than implementation heavy work