This is corporate speak for "LLMs have hit a wall". I mean, it's been obvious for a bit, lately nearly all gains have been from harnesses (or whatever you want to call all the non-LLM bits that make up a chatbot or agent).

If Anthropic and OpenAI were still seeing exponential or even linear gains from scaling they'd be doing it because the rewards to reaching AGI or SGI before everyone else are basically infinite. If both are talking about slowing down it means there's no known path to AGI so they're both going to push the safety angle as an excuse to slow down training new models and take profit.

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baobabKoodaa 5 hours ago | parent | next [-]

You people just never stop, do you? At some point you're gonna have to look back at all the times you said "LLMs have hit a wall" and look at what the progress was since the last time you said that. Please do go ahead and revisit your comment here 1 year later. Embarrassing.

	▲	dismalaf 4 hours ago \| parent [-]
		Why don't you actually read the words and apply a little critical thinking? How often do you hack on actual LLMs? Or do you just use the chatbot or API for your agents? An LLM without internet access or tools is just as useless as a year ago.

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franticgecko3 5 hours ago | parent | prev [-]

That's just so extremely difficult to believe.

Before December 2025 they were still intelligent code autocomplete or Stack Overflow bots, then they started one-shotting serious long horizon tasks. Now they've just solved a millennium prize problem.

In less than a year.

	▲	joshheitzman 5 hours ago \| parent \| next [-]
		> Before December 2025 they were still intelligent code autocomplete or Stack Overflow bots This is false. Coding agents have been usable since at least May of 2025. I can't speak to earlier than that as May last year was when I personally started using them.
	▲	dismalaf 4 hours ago \| parent \| prev [-]
		> started one-shotting serious long horizon tasks. They one-shot tasks for which there's a git clone one-liner, except worse. My experience with them one shotting tasks is that it usually doesn't work if you try anything ambitious. You need agents iterating. And agents iterating isn't an LLM improvement. I did say tooling got better...