151–160 of 620 posts
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>I am learning at an incredible rate with LLMs. I don't believe it. Having something else do the work for you is not learning, no matter how much you tell yourself it is.
It is easy to not believe if you only apply an incredibly narrow world view. Open your eyes, and you might become a believer.
AFAICT this uses a token-counting API so that it counts how many tokens are in the prompt, in two ways, so it's measuring the tokenizer change in isolation. Smarter models also sometimes produce shorter outputs and therefore fewer output tokens. That doesn't mean Opus 4.7 necessarily nets out cheaper, it might still be more expensive, but this comparison isn't really very useful.
We dropped Claude. It's pretty clear this is a race to the bottom, and we don't want a hard dependency on another multi-billion dollar company just to write software We'll be keeping an eye on open models (of which we already make good use of). I think that's the way forward. Actually it would be great if everybody would put more focus on open models, perhaps we can come up with something like the "linux/postgres/git…
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>we don't want a hard dependency on another multi-billion dollar company just to write software One of two main reasons why I'm wary of LLMs. The other is fear of skill atrophy. These two problems compound. Skill atrophy is less bad if the replacement for the previous skill does not depend on a potentially less-than-friendly party.
Not so much atrophy as apathy. I've worked with people who will look at code they don't understand, say "llm says this", and express zero intention of learning something. Might even push back. Be proud of their ignorance. It's like, why even review that PR in the first place if you don't even know what you're working with?
A good dev would've read deeper into the concern and maybe noticed potential flaws, and if he had his own doubts about what the concern was about, would have asked for more clarification. Not just feed a concern into AI and fling it back. Like please, in this day and age of AI, have the benefit of the doubt that someone with a concern would have checked with AI himself if he had any doubts of his own concern...
We dropped Claude. It's pretty clear this is a race to the bottom, and we don't want a hard dependency on another multi-billion dollar company just to write software We'll be keeping an eye on open models (of which we already make good use of). I think that's the way forward. Actually it would be great if everybody would put more focus on open models, perhaps we can come up with something like the "linux/postgres/git…
What open models are truly competing with both Claude Code and Opus 4.7 (xhigh) at this stage?
I've said it before and I'll say it again, local models are "there" in terms of true productive usage for complex coding tasks. Like, for real, there.
The issue right now is that buying the compute to run the top end local models is absurdly unaffordable. Both in general but also because you're outbidding LLM companies for limited hardware resources.
You have a $10K budget, you can legit run last year's SOTA agentic models locally and do hard things well. But most people don't or won't, nor does it make cost effective sense Vs. currently subsidized API costs.
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> we don't want a hard dependency on another multi-billion dollar company just to write software My manager doesn't even want us to use copilot locally. Now we are supposed to only use the GitHub copilot cloud agent. One shot from prompt to PR. With people like that selling vendor lock in for them these companies like GitHub, OpenAI, Anthropic etc don't even need sales and marketing departments!
You are aware that using eg. Github copilot is not one shot? It will start an agentic loop.
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Mind you, a 30B model (3B active) is not going to be comparable to Opus. There are open models that are near-SOTA but they are ~750B-1T total params. That's going to require substantial infrastructure if you want to use them agentically, scaled up even further if you expect quick real-time response for at least some fraction of that work. (Your only hope of getting reasonable utilization out of local hardware in sing…
For a business with ten or more engineers/people-using-ai, it might still make sense to set this up. For an individual though, I can’t imagine you’d make it through to positive ROI before the hardware ages out.
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That is not the entire selling point - so you are very wrong. You very much decide how you employ LLMs. Nobody are keeping a gun to your head to use them. In a certain way. Sonif you use them in a way that increase you inherent risk, then you are incredibly wrong.
I suggest you read the sales pitches that these products have been making. Again, when I say that this is the selling point, I mean it: This is why management is buying them.
I understand why a designer might read this post and not be happy about it. If you don't think your management values or appreciates design skill, you'd worry they're going to glaze over the bullet points about design productivity, and jump straight to the one where PMs and marketers can build prototypes and ignore you. But that's not what the sales pitch is focused on.
My initial experience with Opus 4.7 has been pretty bad and I'm sticking to Codex. But these results are meaningless without comparing outcome. Wether the extra token burn is bad or not depends on whether it improves some quality / task completion metric. Am I missing something?
Sticking with codex. Also GPT 5.5 is set to come next week.
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>we don't want a hard dependency on another multi-billion dollar company just to write software One of two main reasons why I'm wary of LLMs. The other is fear of skill atrophy. These two problems compound. Skill atrophy is less bad if the replacement for the previous skill does not depend on a potentially less-than-friendly party.
Not so much atrophy as apathy. I've worked with people who will look at code they don't understand, say "llm says this", and express zero intention of learning something. Might even push back. Be proud of their ignorance. It's like, why even review that PR in the first place if you don't even know what you're working with?