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Guides/Concept

Open vs Closed Agent Loops

Short answer

Closed loops have clear validation and stop rules. Open loops explore uncertain tasks and need stronger human supervision.

Reviewed 2026-07-14
Inference or recommendation
Classification rule applied to three tasks

The examples below apply one rule: autonomy rises only when success can be checked independently and safely.

Why it matters

Knowing which kind of loop you have tells you how much autonomy is safe. A closed loop with a crisp validator can run semi-autonomously; an open, exploratory loop should keep a human closely in the loop.

Turn uncertain work into a bounded review

  1. 01
    Name the decision
  2. 02
    Separate checks from judgment
  3. 03
    Add limits and exits
  4. 04
    Run one small case
  5. 05
    Review the evidence

Do not force an entire exploratory task into a fake pass/fail loop. Close only the parts that can be checked: source retrieval, link validation, build output, or a fixed comparison table. Pause before the remaining judgment, show the evidence and limitations, and let a person choose the trade-off.

Open, closed, or supervised?

Open, closed, or supervised?
SignalClosed loopSupervised loopOpen work
Success testObjective and repeatablePartly objective, partly judgmentNo decisive test yet
Safe next actionRun inside fixed limitsAutomate checks, pause for judgmentResearch and present options
Human roleApprove the final changeReview at named decision gatesOwn the decision and trade-offs
Stop conditionCheck passes or budget expiresEvidence conflicts or a gate is reachedTime box ends or evidence is sufficient
4 of 4 rows

Choose the smallest safe autonomy level

  1. 01Can an independent check prove the requested outcome?Yes: start with a closed loop
  2. 02Can permissions, files, cost, and retries be bounded before the run?No: keep human control
  3. 03Does any step require product, legal, security, or editorial judgment?Yes: add a named approval gate
  4. 04Would a green check still be misleading after a shortcut?Yes: add evidence and a separate checker

Practical checklist

  • Ask whether success is objectively checkable
  • Treat exploratory tasks as open loops
  • Increase supervision as uncertainty rises
  • Convert open loops to closed ones by adding a validator where possible

A safe example with explicit exits

A documentation refresh can close link checks, spelling, build output, and metadata validation while leaving accuracy and usefulness as a supervised editorial decision.

Stop rule

Stop after two failed validation attempts, any unsupported factual claim, or a requested edit outside the approved documentation paths.

Fallback

Keep the verified source notes and produce a short list of unresolved claims, affected pages, and the exact evidence still needed.

Human approval

A person reviews whether the revised explanation is accurate, genuinely useful, and appropriate to publish; passing automated checks never grants publication authority on its own.

Common failure modes

Running an open loop unattended
Forcing a fake validator onto an exploratory task
Over-trusting autonomy when the goal is fuzzy

Practical evidence

Three loop classifications

Closed: repair one failing CI job

The exact command, expected exit status, scoped diff, and approval gate make success objectively checkable.

Open: choose a product strategy

Evidence can inform the decision, but no machine check can decide which trade-off the organization should accept.

Supervised: refresh a search page

Link, build, and metadata checks can close part of the loop; usefulness, claims, and publication still require editorial judgment.

Related templates

Sources & further reading