From Signal to PR: Anatomy of a Self-Improving Agent — Jason Lopatecki, Arize
Jul 24, 2026 · 20:36
Jason Lopatecki demonstrates how Arize's Signal agent transforms observability from human-clicked dashboards into telemetry for self-fixing systems. The key unlock is pulling production traces and logs as files into a repo—Claude Code works magically with files, not dashboards—so the agent sees the exact code path software took. Signal runs periodically or event-based in a sandbox (VPC-deployed for Uber, Booking), using composable skills to gather context, find root cause, and create a PR. Lopatecki argues you should trace and log ten times more because agents can read that smoke. For the question 'why not just point Claude Code at data?', he explains skills must be well-designed to fetch and format the right data into files. On evals, they run as LLM judges layered on production traces, pre-processing information for the agent to catch known failures and create new evaluators.
