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Joined 11 months ago
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Cake day: November 7th, 2025

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  • Except small local LLMs probably aren’t good enough to carry autonomous tasks correctly (even stuff like Haiku 4.8 from Anthropic makes mistakes quite often) and good luck getting something the size of Opus working in a soda machine. They may not even be able to lay low correctly. But then again these companies have internal models which are atleast couple generations ahead of what is publicly available so maybe they have more efficient smaller ones too? I somehow find it hard to believe but I guess we will see.











  • It can legitimately find some hard to find bugs but it can quite often come up with stuff for which fix would complicate the code substantially without any practical gains (bugs under very hard to encounter situations etc). So it feels like the biggest problem will arose for setups where people drive this fully autonomously where bug fixes also are implemented autonomously. What would be interesting is whether if this improves when they task a seperate agent to assess practical relevance vs increased code complexity affecting code maintainability and increased interaction between subparts. Both maintainability and practicality however are “long horizon” tasks hard to evaluate without real long term experience.