AI Engineer · October 31, 2026

Voice-agent review: separate judge disagreement from agent failure

Voice-agent review: separate judge disagreement from agent failure video thumbnail
Why it matters

Shiv Indap and Brooke Hopkins describe reviewing voice-agent calls against explicit behavioral criteria, resolving disagreements among human reviewers and correcting the automated judge separately from the agent. Confirmed failures are routed to responsible teams and replayed in voice simulations before changes ship. Their private agreement figures do not establish general judge accuracy or regulatory compliance.

My takeaway: Create a written rubric with domain experts and independently label representative calls, including ones the judge passes. Separate ambiguous rules, judge errors and agent errors. Turn confirmed failures into simulations with varied accents, interruptions and noise; retain successful cases to detect regressions. Require the relevant owner’s approval and a controlled rollout for prompt, model or policy changes.
Keep exploring

More curated notes connected through Model Evaluation and AI Engineering.

OpenAI News · framework

Pacing model development in an era of cyber-critical capabilities

OpenAI says preliminary evidence that Astra may meet its Critical cybersecurity threshold led it to pause frontier reinforcement-learning work for two weeks and keep its largest planned run on hold. New safeguards include stronger workload and network isolation, continuous boundary testing, token-level monitoring that escalates suspicious tool activity, and broader alignment checks for deception, reward hacking, and unauthorized access.

OpenAI News · framework

A blueprint for democratic governance of frontier AI

OpenAI proposes a three-part U.S. frontier-AI governance model: harmonize emerging state safety laws into a federal baseline, strengthen CAISI as an evaluation and standards institution, and coordinate a broader resilience program. Proposed controls include severe-risk evaluations, transparency reports, independent audits, safety-incident reporting, model-weight security, whistleblower protection, and periodic technical assessments.

OpenAI News · framework

OpenAI’s Frontier Governance Framework

OpenAI's 22-page Frontier Governance Framework maps its frontier-model processes to California's Transparency in Frontier AI Act and the EU AI Act's general-purpose AI code. It documents lifecycle risk assessment, cyber-offense and other risk tiers, mitigation and residual-risk decisions, critical-incident handling, security risk management, model reporting, external review, responsibility allocation, and change control.