OPEN LINK ↗
// 2h agoOPENSOURCE RELEASE
Developer open-sources AI-trains-AI reinforcement learning pipeline
The ai-trains-ai project implements a meta-learning pipeline where an outer trainer agent writes and dispatches complete training jobs to optimize smaller base models in an inner reinforcement learning loop. By receiving rewards based on the performance uplift of the models it trains, the agent successfully learned to generalize its training skills to unseen task families.
// ANALYSIS
This project provides a fascinating, practical glimpse into recursive AI self-improvement, proving that agents can effectively act as RL engineers.
- –Uses two distinct RL stacks: Tinker for training the agent (outer loop) and prime-rl for training the target models (inner loop).
- –The agent's reward grew from ~0.0 to 0.63 as it learned to optimize configurations and pick better base models.
- –The training capability generalized to a completely unseen, held-out task family (on-call incident triage).
- –The entire project, including model weights, training scripts, and pilot failure write-ups, is fully open-source.
// TAGS
artificial-intelligencellmreinforcement-learningmeta-learningagentopen-source
DISCOVERED
2h ago
2026-07-14
PUBLISHED
6h ago
2026-07-14
RELEVANCE
9/ 10
AUTHOR
Danau5tin
