Thoughts: 1. Some hype-types may have been effusive about AI-assisted coding since ChatGPT, but IMO the commonly agreed paradigm shift was claude code, and especially 4.5, very very recent. 2. Anchoring biases in reaction to hype is still letting one's perspective be defined by hype. Yes the cursor post is a joke, but leading with that is a strawman. This article does not aim to take it's subject seriously, IMO. 3. While I agree the hype is currently at comical levels, the utility of the current LLMs is obvious, and reasons for "skilled" usage not being easily quantifiable are also obvious.

IE, using agents to iterate through many possible approaches, spike out migrations, etc might save a project a year of misadventures, re-designs, etc, but that productivity gain _subtracts_ the intermediate versions that _didn't_ end up being shipped.

As others have mentioned, I think yak-shaving is now way more automated. IE, If I want to take a new terminal for a spin, throw together a devtool to help me think about a specific problem better, etc, I can do it with very low friction. So "personal" productivity is way higher.

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bigstrat2003 5 hours ago | parent [-]

> the utility of the current LLMs is obvious

In that they obviously have no real utility, sure. There hasn't been a paradigm shift, they still suck at programming, and anyone trying to tell you otherwise almost certainly has something to sell you.

	▲	micimize 4 hours ago \| parent [-]
		Based on my direct experience I find this remaining commonality of this opinion surprising, at least with regards to opus in claude code. I'm not as extreme as some who think we can/should avoid touching code or w/e but especially in exploratory contexts and debugging I find them extremely useful. Maybe I should have said "obvious to me," but I guess I just struggle to see how a serious crack at using modern opus in claude code doesn't make it obvious at this point. I'd really recommend trying the "spike out a self-contained minimal version of this rearchitecture/migration and troubleshoot it iteratively until it works, then make a report on findings" use-case for anyone that hasn't had luck with them thus far and is serious about trying to reach conclusions based on direct experience.