Training on production traces: single-trajectory RL may unlock continual learning
rhythmrg · x · 2026-09-22
A key unsolved RL problem: training directly on production traces. Instructive feedback is easy—distill from a strong teacher—but the most valuable production feedback is evaluative (success, score, user acceptance). The standard fix, environment replay (e.g., GRPO), fails when you can't recreate the environment state that generated a trace. New algorithms—Flash-Reinforce, SAO, BPCO—point toward learning from one trajectory per prompt without environment recreation. If they scale on real workloads, they could become a key building block for continual learning.
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