> capabilities have largely converged across foundation models over the last 18 months

For reference, in March '25 the models du jour were Sonnet 3.7, gpt o4 and gemini 2.5 pro. GPT5 was in august '25.

It's been a while since we've heard the old "models have stagnated". Oh well.

It's not "models have stagnated" but "models released at the same time are on the same level". Improvements are still real but the relative gaps between OpenAI, Anthropic, Meta, Grok, Gemini and open models are closer than ever. That doesn't mean progress is slowing down, it's just more widely distributed.

	▲	NitpickLawyer 16 minutes ago \| parent \| next [-]
		Ah, I see. I misunderstood then. The thing about "gains come from the harness" made me think about it in that way.
	▲	alephnerd 27 minutes ago \| parent \| prev [-]
		This, and depending on the workflow and usecase, you don't necessarily need the latest and greatest with the right kind of harness engineering. Like everything in engineering, it's about tradeoffs and what works best for your specific problem.