TokenRhythm's loop: test for weak spots, weight next training batch toward them
PrajwalTomar_ · x · 2026-09-16
Describing step two of TokenRhythm's loop, Prajwal Tomar explains they test the model to find weak spots: if it struggles with coding, tool use, or instructions, the next training batch gets more of that work, then the updated model returns for another round.
The loop isn't continuous yet — it's the direction TokenRhythm is building toward. The thread's premise: when your agent fixes a bug, the underlying model never gets smarter from it, wasting a lot of useful work.
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