The Agent Handoff Pattern: How to Transfer Context Between AI Agents

When one AI agent transfers work to another, the receiving agent starts completely blind. No idea what was tried, what failed, or what context was gathered. The fix: write a handoff.json before every agent-to-agent transfer. The Problem Most multi-agent systems treat handoffs as an implicit 'done' signal. Agent A finishes (or hits a wall), Agent B picks up the task — but with no shared context. Agent B re-discovers what Agent A already learned. It retries steps that already failed. The handoff.json Schema { "task_summary" : "Brief description of the job" , "status" : "partial" , "steps_completed" : [ "Fetched raw data" , "Staged to staging/data.json" ], "steps_failed" : [ { "step" : "Write to production database" , "reason" : "Connection timeout after 3 retries" , "do_not_retry" : true } ], "context" : "Data is pre-validated. Auth token expires at 18:00 UTC." , "next_suggested_step" : "Resume from production write — data already in staging/" , "files_modified" : [ "staging/data.json" ]