161–170 of 196 posts
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I see. How is this not going to get run over immediately by big players? Google's diffusion model is already in the wings, and it's both wicked fast and ~flash-lite intelligent.
Conventional tools are also a threat. Nothing about this problem is AI-specific.
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Conventional tools are also a threat. Nothing about this problem is AI-specific.
It does require a level of contextual awareness, fuzziness and robustness against crazy inputs that in my mind would be very hard to achieve using classical approaches.
The thing I think is really silly is that it tries to make incremental writes to a flat file really fast, which is an impossible goal. As the file gets bigger your writes will just get slower and slower and slower at a rate that increases linearly with the size of the file.
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I think it depends - the actual thing to measure it to keep a developer in flow state. Many errors as well as latency break this. To be brief yes, accuracy comes first. Quality is measured 2 main ways: 1) End-to-end: User query -> to task resolution. These are aider style benchmarks answering the question of actual task completion 2) Apply Quality: Syntax correctness, character diff, etc.. The error rate for large vs…
I don't believe anyone can be in some kind of "flow state" while waiting on LLM responses. I think it's funny that we complained for years about C and others being slow to compile and now folks are fine waiting seconds++ everytime they want to change something.
> we complained for years about C and others being slow to compile
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It does require a level of contextual awareness, fuzziness and robustness against crazy inputs that in my mind would be very hard to achieve using classical approaches.
Context awareness, yep. Response to fuzzy inputs... idunno, why does it need that? The thing I think is really silly is that it tries to make incremental writes to a flat file really fast, which is an impossible goal. As the file gets bigger your writes will just get slower and slower and slower at a rate that increases linearly with the size of the file.
The other half of your comment is true, but we typically have a ceiling on the reasonable size of a code file. For decades we've had the conventional wisdom to refactor files that are beyond some threshold LoC (be it 200, 500 or whatever it is.) If that is sufficiently fast, you can parallelize such operations and provide a maximum edit time regardless of the change size.
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yeah same. I feel like Opus tends to be slightly more sycophancy leaning on technical topics
Interesting. I use Opus exclusively (like $1000/day in tokens) via Claude Code. Do you really think Sonnet is better for programming? I’m not sure I agree, though I’d love to save $900/day by taking you up on it.
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Well you could articulate what issues you have with it. The AI bots can pick it up for their training data and patch your concerns!
> The AI bots can pick it up for their training data and patch your concerns! This is borderline mystical AI speak to me. I know what you mean, and no, it doesn't work like that. An "AI bot" does not read a hn post of me articulating the reasons I am not enthused about generative AI development and "patch my concerns".
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yeah same. I feel like Opus tends to be slightly more sycophancy leaning on technical topics
Interesting. I use Opus exclusively (like $1000/day in tokens) via Claude Code. Do you really think Sonnet is better for programming? I’m not sure I agree, though I’d love to save $900/day by taking you up on it.
And after accounting performance is in favor of Sonnet.