> It hasn’t thought about the problem at all. It’s pattern-matching against its training data and producing the most plausible-sounding response.

The article kind of lost me here. Agents are way more than that, today. And the author knows it, as later it says stuff like

> Claude will never do this. It’s trained to be helpful.

But the first phrase just tell me author just have a deep dislike for agents and it's looking for rationalizations for that feeling.

Part of the criticism is on point, sure. But if it "being trained to be helpful" is a problem, it's fixable. It can "be trained to be more critical".

Later:

> But it wasn’t designed for your team. (..) It was designed for the median of everything Claude has seen. A generic best practice for a generic problem at a generic company. Which is to say, it was designed for nobody.

That's non-sense. Anybody who understand algorithms know that, sure, on a first instance you have a "good algorithm" that has a good performance on average, or in worst-case. But then, you can design algorithms that are adaptive to the input. Same applies here.

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sevenzero 4 hours ago | parent [-]

>Agents are way more than that, today.

Not really though. They just iterate more and more.

	▲	kgeist 4 hours ago \| parent [-]
		Isn't that how many people program too? I remember some idea or pattern from previous projects, or something I read about on the internet. Then I code it in the most straighforward way, whatever comes to mind first. Then I sit back and analyze: does it look good architecturally? Do I like it? Does it even compile? Then I rewrite some parts to make it more sound. Rinse and repeat, until I'm satisfied. I usually don't come up with entirely novel ideas on the first attempt. I usually just rehash known concepts over the course of many iterations.