Short answers to what readers ask most about this topic.
Why multi-agent systems get stuck bouncing a task back and forth, and how one orchestrator, clear ownership, and hard caps design the loop out for good.
Matthews Wong
Software Engineer
Key Takeaway
An infinite handoff loop is when two or more agents bounce a task back and forth without finishing, each deferring to the other. It comes from vague ownership and missing stop conditions. Fix it with a single orchestrator that owns the decision, explicit termination rules, and a hard iteration cap that ends the run.
Multi-agent systems fail in a distinctive way. Instead of crashing, they get polite: a router hands the task to a specialist, the specialist decides it is out of scope and hands it back, the router hands it on again, and the two spin until you kill the process or the bill scares you off.
This is the handoff loop, one of the most common failure modes once you move past a single agent. This guide covers why it happens, how to design it out, and how to add the runtime guards that stop a loop before it drains your token budget.
A handoff is one agent passing control, plus context, to another. In a healthy system handoffs flow toward completion. In a broken one they form a cycle: agent A defers to B, B defers back to A, and neither owns the moment where the task is declared done.
The loop almost always traces back to one of a few root causes:
The most reliable fix is structural: a single orchestrator owns the flow, and specialists are workers it calls, not peers that call each other. Workers return results to the orchestrator; they never hand off sideways. Anthropic describes this orchestrator-worker shape as a default for multi-agent work, precisely because control stays in one place.
Encode that hierarchy in the loop itself, with a guard that ends the run rather than letting it cycle:
# Orchestrator loop, pseudocode
for step in range(MAX_STEPS):
result = worker.run(task, context)
if result.done:
return result # success: stop here
if seen(result.state):
abort("repeat detected") # loop guard
task, context = plan_next(result)
return abort("hit MAX_STEPS") # hard capWrite each worker's system prompt to end with a return, not a handoff. If a worker cannot complete its task, it should report that failure back to the orchestrator with a reason, not pass the task sideways to another worker it happens to know about.
Structure prevents most loops; explicit stop rules catch the rest. Every agentic run needs conditions under which it must end:
Many loops are really amnesia. When a handoff passes the task but not the reasoning behind it, the receiving agent re-derives the situation, reaches a different conclusion, and hands it back. Each agent starts cold, so the system never converges.
The fix is to treat the handoff payload as a contract: what was tried, what was decided, and what the receiver is expected to produce. A well-formed handoff moves the task forward; a bare one invites the receiver to second-guess and bounce it back.
A retry is not a fix. Wrapping a looping system in automatic retries multiplies the cost of the bug instead of removing it. Find the missing stop condition or the ambiguous ownership first; a loop that reliably terminates at a cap is still a loop you need to design out.
You cannot fix a loop you cannot see, so instrument the system before you let it run unattended:
Infinite handoff loops are a design smell, not a mystery. Put one orchestrator in charge, give every worker a contract that ends in a return, and back it all with hard iteration and budget caps. The loop that cannot happen is worth far more than the retry that papers over it.