Multi-agent AI pipelines have a visibility problem - they run silently for 30-60 seconds, and you have no idea which step is active, how long it's taking, or where it broke 🥴 Agent callbacks are a simple way to fix that... 🧵👇

2/5 Most agent frameworks let you attach a "before" and "after" hook to each agent. - The "before" hook fires right before the agent starts. - The "after" hook fires when it's done. That's all there is to it — two hooks per agent.

3/5 With those two hooks, you can log which agent is running, record when it started, and print how long it took when it finishes. Instead of a blank terminal for a minute, you get: "Researcher starting..." "Researcher done (12.3s)" "Analyst starting..."

4/5 The "before" hook can also skip an agent entirely. If cached results already exist from a previous run, the hook finds them and returns the data directly - the agent never runs. That's agent-level caching with zero changes to the agent itself.