How to Generate an Audit Trail for AI Agent Actions (With Visual Proof)

How to Generate an Audit Trail for AI Agent Actions (With Visual Proof) You've deployed an AI agent to handle customer refunds. It works perfectly in testing. But your compliance officer asks: "How do we prove what the agent actually did in the browser?" You show them text logs from LangSmith or Langfuse. They're not satisfied. Text logs tell you what the agent claimed to do. Visual proof shows what it actually did. This is the gap between logs and compliance. The Problem: Text Logs Aren't Audit Proof Observability platforms (LangSmith, Langfuse, OpenTelemetry) capture: Agent decisions Tool calls and responses Token usage Latency metrics But they don't capture what the agent actually saw or clicked. Example: Your agent logs say "clicked refund button." But did it? What was on screen? Did the page load correctly? For compliance (HIPAA, SOC 2, PCI-DSS, EU AI Act), you need visual evidence. The Solution: Screenshot After Each Agent Step Add a screenshot after every agent action: import an