Real-Time Monitoring for AI Agents: Beyond Log Streaming

Most agent monitoring is "log everything and grep later." That's not monitoring — that's archaeology. What We Actually Need Live execution view — Which agent is running right now? State inspection — What data is Agent C holding? Failure forensics — Why did Agent B timeout? What were its inputs? Performance metrics — Per-agent latency, token usage, error rate AgentForge's Monitoring Stack Execution Trace (Structured JSON) Every pipeline run generates a trace: { "run_id" : "uuid" , "status" : "com