Applied Compute uses Jev to auto-cluster failure modes in RL training traces
rhythmrg · x · 2026-09-24
Applied Compute shares how they use Jev across their product, with the standout use case being monitoring traces generated during RL training:
- RL training produces billions of tokens of rollout traces; manually reading them misses agent-level failures like reward hacking and hallucinations
- Team member @brylee10 built an automated failure-mode clustering system with Jev on their platform
- Jev serves as a cheap, high-recall first pass over billions of rollout tokens to surface errors at scale
- The team wants to automate more manual work into the product to focus on the hardest, most creative parts of training
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