| ▲ | tuesdaynight 4 days ago | |
I don't agree with using your credentials to show your code quality, but I don't doubt you have better standards than most developers. That said, stop trying to change their minds. Antirez was a good at programming until he started coding using AI only. The same will be said about Carmack and Linus. What they are saying is increasingly difficult to defend, but they will do it anyways. I see the same arguments at my job, and I just gave up arguing against | ||
| ▲ | LatencyKills 4 days ago | parent [-] | |
I mention my background because it is relevant context: I spent nearly 30 years building software used by billions of people. If you use Windows or macOS, you have likely used code I helped ship. I’m not going to apologize for that experience or pretend it does not inform my judgment. Some engineering problems (such as designing a performant thread-quantum algorithm) require depth accumulated over years of working on real systems at scale. That is not elitism; it is simply how specialized expertise works. Experience is unevenly distributed, and that matters when evaluating technical claims. When I say I trust LLM generated code, I mean that in a qualified, engineering sense. I do not treat an LLM as a slot machine: enter a prompt, paste the output, and hope. I use a deliberate workflow for decomposition, prompting, review, testing, validation, and integration. Developing that workflow took substantial time and experimentation. The useful question is not “Can an LLM write code without oversight?” It obviously cannot, at least not reliably for nontrivial work. The question is whether an experienced engineer can build a process that makes LLM output trustworthy enough for particular classes of work. In my experience, the answer is yes. But the process, judgment, and willingness to do the work are the hard parts. | ||