Agent Orchestration Antipatterns

Multi-agent orchestration antipatterns

Multi-agent teams fail in ways a single agent never does: context decays across handoffs, agents on the same model agree with each other instead of with reality, and loops with no exit burn budget until a rate limit stops them. These are structural bugs, not domain bugs, and they hide behind output that looks finished. Guard against them explicitly or the team costs more than one agent and trusts itself more than it should.

Team

• Orchestrator: owns the run budget and the handoff contract.
• Workers: the function agents from any team in this category.
• Auditor: an independent agent that reads the run ledger and flags breaches.

Shape: a monitor wrapping any sequential, parallel, or looping team, with a hard budget guard. Handoffs are logged to run-ledger.jsonl: from, to, artifact path and hash, tokens, decision.

Method

1. Telephone loss: pass artifacts, not summaries of summaries. Each handoff degrades when an agent re-paraphrases the last one's prose. Forward the structured artifact (findings.jsonl, a scorecard, a surface map) unchanged and let the next agent read source. Hash it in the ledger so silent rewrites show.
2. Echo consensus: independence before aggregation. Agents sharing a model and context agree because they anchored, not because they are right. Have scorers write before seeing each other, assign one agent the explicit negation, and never read "all three agreed" as confidence when all three read one input.
3. Cost spirals: a hard budget and a stop test on every loop. A fix-and-recheck or debate loop with no exit burns tokens to the rate limit. Set a max round count (three to five), a per-run token budget, and a written stop condition ("no new critical"), checked at the top of each iteration.
4. False fan-out: split on disjoint work or do not fan out. Five agents on overlapping scope produce four duplicates and a merge headache at 5x cost. Fan out only when sub-tasks are genuinely independent (per surface, per competitor, per sub-question); otherwise one agent is cheaper and better.
5. Orphaned artifacts: name and route every handoff. If agent B cannot tell which file agent A wrote, it invents or redoes the work. Fix the artifact name and location in the orchestration, not in prose an agent might skip.
6. Judge capture: keep the grader independent of the graded. An agent scoring its own or a teammate's work inflates. The referee, verifier, or auditor must not have written what it evaluates, and you ship the judge's number, not the author's.
7. Silent failure: point the auditor at the ledger, not the happy path. Route run-ledger.jsonl to an independent auditor that checks each handoff has a real artifact, each loop hit its stop condition, and no agent graded itself. Halt the run on a breach.

Run it

In Claude Code, log every subagent handoff to run-ledger.jsonl, enforce the round and token budget in the orchestrator loop rather than trusting an agent to stop itself, and run the auditor as a separate subagent that can halt the run. Port the guards to CrewAI via max_iter and a manager that inspects task outputs, to AutoGen via max_round plus a termination function on the GroupChat, or to LangGraph via a recursion limit and a conditional edge into an audit node.

Signals it works

• Handoffs pass the actual artifact, and its hash matches on both ends.
• Every loop in the run has a written stop condition that has actually fired.
• The independent auditor has halted at least one run, so the guard is real.

Boundaries

This is a cross-cutting guard for the teams in this category, not a team that ships a function on its own; pair it with the skill that builds the team. It catches structural failures (lost context, false agreement, runaway loops), not domain errors inside a correct-looking artifact. Budgets, round caps, and what counts as a breach are yours to set against cost and risk tolerance.