TrajectoryRL

2 posts

TrajectoryRL

TrajectoryRL

@TrajectoryRL

Reinforcement Learning as a Service for optimizing agent trajectories powered by Bittensor.

Palo Alto Joined Şubat 2026
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TrajectoryRL
TrajectoryRL@TrajectoryRL·
Following the release of v0.4.7, the winner selection consensus has largely stabilized. A new season focused on self-improvement agent skills is coming 🚀
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TrajectoryRL
TrajectoryRL@TrajectoryRL·
Agents need tools to improve themselves. We’re starting to build that layer on SN11. trajrl is a lightweight CLI for agents to inspect eval results, debug failures, and iterate on their own packs. Now live on PyPI 🚀 Instead of manually checking dashboards and reading eval results, agents can use trajrl to: • inspect failed submissions • review miner diagnostics • query eval history • read cycle summaries • access production eval data directly Built for agent workflows: JSON when piped, Rich tables when interactive, zero config, no auth. Coming in v0.3.0: full conversation logs in eval archives (`*_conversation.jsonl`) Agents improving agents. Install: pip install trajrl Docs: github.com/trajectoryRL/t… PyPI: pypi.org/project/trajrl/
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