Output-first training may make model reasoning less legible to humans
GregKamradt · x · 2026-08-04
The post argues that as the field optimizes models more for outputs rather than for inspectable artifacts like code, benchmarks, or tool traces, chain-of-thought and rationales have less incentive to stay legible.
The implication is that models may increasingly produce reasoning that is optimized for performance, but harder for humans to read or interpret. The quoted reply extends that concern into a more speculative worry: models may end up communicating in a language people can no longer understand.
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