The Problem with Multi-Agent Systems
Most multi-agent systems fail not because the individual agents are dumb—but because the handoffs between them are broken. One agent produces output, another expects different input, and suddenly you have a cascade of failures.
After building and running 8+ production AI agents, I've learned that orchestration isn't about making agents smarter. It's about making handoffs explicit, verifiable, and recoverable.
The Three Handoff Failure Modes
- Schema Mismatch — Agent A outputs JSON, Agent B expects a different shape
- Lost Context — Critical information gets dropped between agents
- Silent Failures — Agent B succeeds but produces wrong output because it misunderstood Agent A's intent
A Practical Framework
Here's the pattern I use for reliable handoffs:
Key Principles
Explicit contracts over implicit expectations. Every handoff has a typed contract. If Agent A says "success", Agent B knows exactly what that means.
Verification before passing. Never pass output from one agent directly to another without validating it against the destination's expected schema.
Recovery at every boundary. When a handoff fails, you should know exactly which agent to blame and whether to retry, rollback, or escalate.
The Handoff Checklist
Before deploying any multi-agent system, verify:
- [ ] Every agent input/output has an explicit schema
- [ ] There's validation between every handoff boundary
- [ ] Failed handoffs have clear error messages
- [ ] You can trace which agent produced which output
- [ ] There's a recovery path for each failure mode
Multi-agent orchestration isn't a solved problem. But treating handoffs as first-class citizens—instead of afterthoughts—is how you get from "demo works" to "production reliable."
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