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ragequittah 2 hours ago

If you haven't seen the (massive) increases in utility I'd wager you haven't been using the tools much.

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abalashov an hour ago | parent [-]

So I'm holding it wrong?

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ragequittah an hour ago | parent [-]

My guess is you're barely holding it at all if you haven't seen several more uses for it in the last year or so.

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abalashov 41 minutes ago | parent [-]

I didn't say that. However, the utility delta in the "early days" was infinitely more palpable. By the time GPT-5 or GPT-6 came out, these models were just doing things they did before more accurately, with more context integrity across long-horizon tasks, etc., not doing things they couldn't do before.

This is true of every frontier model. The real agentic coding breakthrough in Claude land was around Opus 4.5 or so, though it's hard to say if that might have just been coeval with the release of the Claude Code harness.

On the Chinese front (my preferred landscape because of the open weight aspect, not because I'm Chinese), Kimi has been perfectly viable since K2.5, DeepSeek since however many major releases ago, and GLM and MiMo and the rest of them too, although they all achieved breakout moments of publicity at different times. There's no denying that every release brings improvements, but if we're going to be honest, they're fairly marginal.

	▲	ragequittah 12 minutes ago \| parent [-]
		They seem more marginal because the models are already capable of so much. But there was a turning point about November of last year if I recall where software developers I know went from "lol look at how this thing codes, my job is safe" to "oh no". And the models back then were actually pretty bad at many things compared to Astra or Opus 5.5. You're right that many of the less capable / open weights models are very good themselves, but that's part of showing how much more capable the frontier models are becoming. Cheaper (smaller) models are able to do the same things, in many cases better, as the way larger models were able to do a year ago. The efficiency is getting way better alongside the 'intelligence'. That'll also cause the models to become much faster over time which is the real improvement I'm waiting for. I think a part of why many people aren't seeing big deltas if they're using it for code and they're actually coders is we actually sit down and reason out the project with the LLM. Someone who knows nothing about coding ~1 year ago wouldn't come even close to the kind of app they'd get now with the same instructions. If you just give it a task like "help me decompile this game" without knowing a whole lot about decompiling suddenly in the last 3 or so months you start to get some half-decent results. The sea-change I see lately is about lifting up the people who couldn't do these things before more than the people who could. And I actually see problems coming from that already as people I've met think they can make enterprise grade software if they just tell their LLM to make it safe.