Agent Reliability Lab
An experimental platform for verification, recovery, and observability in multi-step AI agents.
Overview
This placeholder project explores a traceable execution model for agent plans, tool calls, and outcomes, with recovery paths for timeouts, partial failures, and false-success reports.
Engineering highlights
- Evaluates completion with acceptance rules, not exit codes
- Persists checkpoints for resumable long-running work
- Reconstructs agent decisions from structured events