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| ▲ | a2ff6eeb0 38 minutes ago | parent [-] | | Feel free to do your own analysis -- my informal experiments backs this up, though. I see worse results when I try to do anything in an unpopular language. It makes sense, needing to train the model on things that aren't already in its weighs takes up valuable context. Until we have models that update their weights based on what they've seen in their recent sessions and learn like people, this will be a problem. For now, though, between the results I'm seeing here, and the lack of need to look at code, I think this kills off any reason for me to use less popular languages. | | |
| ▲ | jauntywundrkind 34 minutes ago | parent [-] | | Your attempt was probably pretty, ahem, weak. How much support would you say you gave your goes, before you threw in the towel? I don't think there's really ever a downside to leaning in and making use of a language or system that works for you. Trying to tell people they should just use the popular thing is, imo, bad advice to turn hackers and experimenters into boring people. | | |
| ▲ | a2ff6eeb0 32 minutes ago | parent [-] | | A day or so for each of the oddball languages; again, I'm still waiting for an argument on why I'd bother, since the entire point of an agentic system like this is that I don't have to read the code. Experiment with the AI, sure, but you've got a pretty high burden of proof to show that AI is going to pick it up without a high per-prompt token cost. AI changes the constraints here for now, since it can't permanently learn things. I'm waiting until that changes, but right now it's better to use what it knows out of the box if you want good results. A better language doesn't buy me anything other than performance; the reason to stick an AI in here is to remove interactions with the code. I don't care what the AI chooses to use, as long as it gets results. |
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