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I feel like the opposite is true but maybe the issue is that we both live in separate bubbles. Often times I see people on X and elsewhere making wild claims about the capabilities of AI and rarely do they link to the actual output.

That said, I agree that AI has been amazing for fairly closed ended problems like writing a basic script or even writing scaffolding for tests (it's about 90% effective at producing tests I'd consider good assuming you give it enough context).

Greenfield projects have been more of a miss than a hit for me. It starts out well but if you don't do a good job of directing architecture it can go off the rails pretty quickly. In a lot of cases I find it faster to write the code myself.

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osn9363739 a day ago | parent [-]

I'm in the same bubble. I find if they do link to it it's some basic unimpressive demo app. That said, I want to see a video where of one of these people that apparently 10x'd there programming go against a dev without AI across various scenarios. I just think it would be interesting to watch if they had a similar base skill & understanding of things.

	▲	BeetleB a day ago \| parent [-]
		> That said, I want to see a video where of one of these people that apparently 10x'd there programming go against a dev without AI across various scenarios. It would be interesting, but do understand that if AI coding is totally fantastic in one domain (basic automation scripting) and totally crappy in another (existing, complex codebase), it's still a (significant) improvement from the pre-AI days. Concrete example: A few days ago I had an AI model write me a basic MCP tool: Creating a Jira story. In 15 minutes, it had written the API function for me, I manually wrapped it to make it an MCP tool, tested it, and then created tens of stories from a predefined list, and verified it worked. Now if you already know the Jira APIs (endpoints, auth, etc), you could do it with similar speed. But I didn't. Just finding the docs, etc would take me longer. Code quality is fine. This is not production code. It's just for me. Yes, there are other Jira MCP libraries already. It was quicker for me to write my own than to figure out the existing ones (ditto for Github MCP). When using LLMs to solve a coding problem is faster than using Google/SO/official docs/existing libraries, that's clearly a win. Would I do it this way for production code? No. Does that mean it's bad? No.