Feedback on GPT-5.6-Sol Coding Performance
andrew_n_carr · x · 2026-07-14
This shares observations after using GPT-5.6-Sol on roughly 30 billion tokens. The author describes the model as highly "OCD": it gets triggered by random minor issues in the codebase, repeatedly writing tests to fix them. Iterative development is sluggish, especially during long build times, even in fast mode. Worse, after two compaction cycles, it starts chasing nitpicky or irrelevant goals the user never asked for, losing focus on the main task. The author notes this isn't just a harness issue, as switching to codex, pi, or opencode showed no fundamental difference, pointing to a model-level flaw. The takeaway: AI-generated code flaws often have a delayed effect, only surfacing after multiple actual development cycles in the codebase.
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