Multi-Agent Debugging
ELI5 — The Vibe Check
Multi-agent debugging is figuring out which AI agent broke things when five of them were running in parallel. Worse than normal debugging because each agent has its own context, logs, and token trail. You need a unified view.
Real Talk
Multi-agent debugging is the emerging discipline of diagnosing failures in systems with multiple concurrent or interacting AI agents. Challenges: interleaved logs, non-deterministic execution order, context boundaries, and cascading failures across agents. Tools include LangSmith, AgentOps, and Helicone. Best practices: trace IDs across agents, deterministic replay, and structured logging of tool calls.
When You'll Hear This
"Multi-agent debugging is 3x harder than single-agent." / "Set up trace IDs before you hit multi-agent debugging hell."
Related Terms
Multi-Agent
Multi-agent means multiple AI agents working together, each handling a different task.
Observability
Observability is the ability to understand what's happening inside your system from the outside, using three types of data: metrics (numbers), logs (events...
Swarm Debugging
Swarm debugging is multi-agent debugging, but for flat peer-to-peer agent swarms.