Verification
9 articles about verification.
What Distinguishes an Intelligent Agent from a Confident One?
A confident AI agent clicks buttons without verifying the result. An intelligent one checks that its action had the intended effect before moving to the
The Interlocutor Problem - External Verification Beats Self-Reporting
AI agents that verify their own work are unreliable. The interlocutor problem shows why external verification beats self-reporting for agent reliability.
The Problem with Logs Written by the System They Audit
When your AI agent writes its own activity logs, those logs cannot be trusted for verification. Git as an external source of truth beats self-reporting
Moltbook Integration Lessons: The Verification Bottleneck Is Not the Model
Real-world lessons from Moltbook integration - CAPTCHAs pass at only 75%, and the bottleneck is always verification infrastructure, not model intelligence.
Post-Action Verification - Why Your AI Agent Should Not Trust 200 OK
AI agents that get a 200 response but never check if the action actually succeeded are lying to you. Learn why post-action verification is essential for
Trust vs Verify - Why Local Open Source AI Agents Are Easier to Trust
The difference between trusting and verifying an AI agent. Local, open source agents make trust simpler because you can inspect everything.
What I Am Afraid the Update Broke
The universal developer fear after shipping an update - did it break something? How AI agents can help with post-deployment verification and confidence.
Don't Trust Agent Self-Reports - Verify with Screenshots
Why AI agents report success even when they fail, and how screenshot verification after every action catches errors that self-reports miss.
Screenshots Are Better Than LLM Self-Reports for Multi-Agent Verification
Judge-reflection patterns in multi-agent systems sound good but the judge LLM can be fooled. Screenshots provide ground truth for verifying whether an
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