Build a DVR for AI Agents: Episode Replay UI That Actually Works

Build a DVR for AI Agents: Episode Replay UI That Actually Works Your AI agent made 147 decisions in 3.2 seconds, then failed — and you have no idea which decision broke everything. The Problem: AI Agents Are Black Boxes Moving at Light Speed Here's what happens when your CrewAI agent crashes at 2 AM: # Your agent's final words ERROR : Task execution failed after 147 LLM calls Context : " something went wrong lol " Traceback : < unintelligible garbage > You know it made 147 LLM calls. You know it failed. You don't know: What it was "thinking" at step 73 Why it decided to call the wrong API at step 112 What context it had (or lost) when everything went sideways Traditional logging gives you timestamps and error codes. What you need is a DVR that lets you scrub through your agent's entire "episode" — see every thought, decision, and API call in chronological order. With context. This isn't just debugging. It's time travel for AI systems. Architecture: How Agent DVR Actually Works graph T