VIII · Safety & ControlMature★★

Approval Queue

also known as Async Approval, Supervisor Inbox, Approval Inbox

Queue agent-proposed actions for asynchronous human review while the agent continues other work.

This pattern helps complete certain larger patterns —

  • specialisesHuman-in-the-Loop★★— Require explicit human approval at defined points before the agent performs an action.
  • used-by[crawl-walk-run-automation-gating]
  • used-byProgressive Delegation★— Stage the human-to-agent handoff over time: the agent starts producing drafts a human always reviews; its autonomy expands action-by-action as measured trust accrues.
  • used-byCost-Aware Action Delegation★— Classify every agent action by risk/cost and route each tier to a different approval policy, bounding the autonomy surface per-action instead of by one global flag.

Context

A team is operating a long-running agent product that performs many actions per session — sending emails, posting messages, opening tickets, scheduling meetings — where a non-trivial fraction of those actions need a human to look at them before they ship. Stopping the entire agent loop after every proposed action while a human gets around to clicking approve would reduce throughput to a trickle and waste the parallelism the agent could otherwise exploit.

Problem

If the agent calls the human and blocks until they respond on every gated action, the system is only as fast as the slowest reviewer and the agent sits idle between clicks. If the team removes the gate to keep the agent moving, unsafe or wrong actions ship before anyone has a chance to look at them. A naive design forces a choice between slow-and-safe and fast-and-dangerous, with no middle path that preserves human authority without holding the whole loop hostage to it.

Forces

  • Async approval adds wall-clock delay before action lands.
  • Approval inbox can become unmanageable at scale.
  • Race conditions if the world changes while approval is pending.

Example

An email-drafting agent prepares replies to 80 inbox messages overnight. Rather than send them automatically (risky) or block waiting on each one (slow), the agent writes them to an approval queue. In the morning the user reviews 80 draft replies and clicks 'send' or 'reject' on each. The agent kept moving through the inbox while waiting for the human.

Diagram

Solution

Therefore:

Agent emits proposed action to an approval queue with context. A human (or supervisor agent) reviews the queue and approves or rejects. Approved actions are executed by the agent or by a runner. The agent can continue parallel work while waiting; some workflows pause specific branches.

What this pattern forbids. Actions in the approval queue may not execute until the approval status is set to approved.

And the patterns that stand alongside it, or against it —

  • complementsCompensating Action★★— Pair every irreversible-looking agent action with a compensating action that can undo or counteract it.
  • complementsConversation Handoff to Human★★— Transfer the entire conversation thread from agent to human operator, with state transfer and return primitive.
  • complementsSimulate Before Actuate★— Before issuing an irreversible action, run a deterministic simulation that computes pre-conditions, invariants, and expected deltas; require a verifier — automated or human — to green-light the simulated outcome before the real command is sent.
  • complementsDry-Run Harness★— Simulate planned actions (and their projected side effects) without committing them, surfacing a reviewable diff before any commit.
  • complementsSynchronous Execution-Plan Confirmation★— Agent synchronously emits its full execution plan for user confirmation before any side-effect step, and provides asynchronous operation recordings for post-hoc review.
  • complementsPipeline Triad Pattern★— Staff each pipeline stage with a triad — Creator generates an artifact, Critic finds flaws, Arbiter makes a binding PASS/FAIL/PARTIAL decision — with four explicit human gates between stages.
  • alternative-toHuman Reflection★— Reflection loop that explicitly collects human feedback (not approval) on agent plans to improve them, distinct from approval gates where the human only says yes/no.
  • complementsPolicy-Gated Agent Action (KRITIS)★— Each agent action passes through a policy gate (NIS2, EU the agent Act, BSI rules) and is tagged with Run ID + Model Digest + Policy Hash for WORM-audit reconstruction.
  • complementsTwo Human Touchpoints★— Place exactly two human-in-the-loop checkpoints in agentic pipelines: one at content selection and one at final review before publication.
  • complementsAutonomy Slider★— Expose agent autonomy as a continuous adjustable parameter so the same codebase can span scripted assistant to fully autonomous worker without re-architecting.
  • complementsCorrigible Off-Switch Incentive·— Design the agent so being shut down or overridden by a human carries positive expected value, because the human's intervention is itself evidence the current objective is mis-specified.
  • complementsInterruptible Agent Execution★— Treat pause, resume, and cancel as a first-class control surface on every long-running agent so users can halt expensive or off-track trajectories mid-task while state is preserved for resumption.

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