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LLMs have been good at knowing what's in the manual from v1.0. Super good at that. Pretty good translators. Pretty good at doing things that have been done a million times before, like your CRUD app. Super mediocre at everything else.

LLMs as things that know what's in the manual are AAA+. Extremely helpful. Very good at making a rough draft of something filled with a lot of stupid mistakes and no new abstractions. That's what your transparent window thing is. Something that you could never ship, is probably too big and doing senseless things for no intelligible reason, and definitely has bizarre bugs.

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What in the world are you talking about? I was literally an senior engineer on the Windows Kernel team, the Visual Studio team, and the Xcode team at Apple.

This application, named Seymore, is being evaluated for purchase by several tech companies. (It helps having good industry contacts)

There was a ton of interesting engineering required to make this work at 60 fps+ without resorting to hacks or using private APIs. Most macOS engineers wouldn't even know where to start.

I've shipped code that is used by billions of people and all you just did was spew a bunch of bullshit. As someone who has built their own LLM from scratch, I have an extremely good idea of what they can and can't do.

If you don't know how to use these tools, you'll end up with crap. If you DO know how to use them, they are incredibly useful.


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


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.




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