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by Aurornis
20 days ago
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We're in the messy transition period where our old indicators of a promising GitHub project are too easily replicated by someone letting Claude Code run for a few days. A year ago it would have taken someone months of nights and weekends effort to get this much code up and running. That person would have developed a good intuition for the architecture and where it should go. Now Codex or Claude can bang it out in a couple days. You can try to have it do spec documents, code reviews, and cleanup passes but with today's tools these projects reach a point where it's just a swirling mess of pieces duct taped together in a way that passes tests. In my experiments, you quickly reach a point where the usable context depth (which is less than the 1M limits) keeps overflowing before you can get usable refactors in, and you're just going in circles. I know it's theoretically possible to avoid these problems, but in practice you get spaghetti projects like this. |
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Previous models both GPT and Claude would struggle with the larger picture more. Pretty quickly they’d do one off hacks. Eventually they’d code themselves into a wall if you weren’t careful.
Haven’t hit that wall with GPT-5.5 yet. New changes or improvements on a GUI library I’m building seem to be constant in time per feature.
Though I’m talking only 10k’s of LOC. Also I’m using Nim which is both strongly typed and concise.