Why AI Agent Outputs Need Adversarial Review (and...

The Problem: Agents Grading Their Own Homework If you’re running LLM agents in production — whether with LangChain, CrewAI, or custom pipelines — you’ve probably built some kind of output validation. Maybe a second LLM call checks the first one’s work. Maybe you parse for structural issues. Here’s what I kept finding: LLM-based self-review has a systematic leniency bias. When you prompt an LLM to review output from another LLM (or itself), it overwhelmingly approves. The reviewer and generator s