Agents Need White-Box Instruments, Not Judges

About this session

Enterprises are deploying AI agents that finish tasks and report success — and a measurable fraction of those reports outrun the evidence: claims contradicted by the agent's own trace, "verified" work where verification never ran. Today's default answer is to ask another LLM to judge — an opinion with no error bars, from the same kind of system being audited. Faberlens takes the instrument path: white-box measurement, calibrated to each customer's baseline and delivered with measured error rates — the difference between a second opinion and a gauge. The product is an audit queue, not a vibe: "of these 1,000 runs, review these 20 — and look exactly here." And overclaimed work is only the first instrument: the same approach reads manipulation — prompt injection, confused-deputy — anywhere an agent's account of its own actions can't be trusted. Ten minutes: the live triage workflow, the learning loop that turns human review into better-behaved agents, and why white-box assurance becomes the system of record for the agentic enterprise. Live demos at our booth.