An approval queue lets an AI agent prepare routine work while pausing for a person only when a proposed action meets a review rule. The practical pattern is to define which actions need approval, present reviewers with the exact proposal and enough context to judge it, persist the paused workflow, and resume or handle rejection after a decision. The documentation supports this architecture, but it does not establish that a particular implementation reduced interruptions or describe the author’s codebase.
What an approval queue changes
Without a deliberate boundary, an agent’s tool workflow can make a person approve too much—or let consequential actions proceed without review. An approval queue separates preparing an action from carrying it out:
- The agent proposes a specific tool action.
- Policy determines whether that action can proceed automatically or requires a human decision.
- If review is required, the workflow pauses and makes the pending decision available to a reviewer.
- The system retains the run and decision context while it waits.
- Approval resumes the workflow; rejection must lead to a defined alternative, such as stopping or asking the agent to revise its plan.
This is a workflow boundary, not simply a notification. The queue is useful only if the pending action is identifiable, the run can wait safely, and the decision can reach the paused workflow.
Decide what deserves a human decision
Start with policy: identify the tool actions or workflow steps that require judgment, then let consistent, machine-checkable conditions handle cases that do not. OpenAI describes guardrails and human approvals as complementary rather than interchangeable controls. Its guidance also recommends showing the reviewer the exact proposed action and only the context needed to evaluate it. OpenAI’s guide to guardrails and human review discusses that distinction.
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- Use automatic checks for conditions that can be evaluated consistently.
- Require human review for actions designated by policy as needing judgment.
- Make each request concrete: identify the proposed action and include enough relevant context for a decision.
The sources do not prescribe a universal list of actions that need approval. That boundary depends on the workflow’s policy; do not assume a framework’s approval feature decides it for you.
Make the pause durable and actionable
A reviewer may not respond immediately, so the workflow needs to preserve the pending run and the context needed to continue. OpenAI’s Agents SDK documentation describes approval interruptions and serializable run state that can be saved and resumed after a decision. AWS’s guidance describes saving decision context in durable storage before notifying a reviewer. OpenAI Agents SDK human-in-the-loop documentation and the AWS Well-Architected Agentic AI Lens cover these aspects of the pattern.
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The queue also needs a response path. AWS describes delivering a task token to an approval application through a channel such as a queue, email, or webhook. The application returns the reviewer’s decision so the workflow can resume or fail. In other words, a notification by itself is not the approval mechanism: the decision has to be associated with the waiting workflow.
How framework approval flows differ
Framework documentation describes different primitives for implementing the same broad pattern. Compare how each represents policy, the pause, saved state, reviewer context, and continuation rather than assuming that the products behave identically.
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| Implementation | Pause and decision representation | State and continuation | Source |
|---|---|---|---|
| OpenAI Agents SDK | Approval interruptions for tool actions. | Run state can be serialized and resumed after the approval decision. | Agents SDK documentation |
| Microsoft Agent Framework Workflows | A workflow pause and a request-info event that carries approval content. | The documented workflow pauses for human input; consult the framework documentation for its event and resumption details. | Microsoft HITL documentation |
These documented differences are useful comparison points, not evidence that one framework is universally better. Before choosing, check how approval policy attaches to tools or workflow steps, what state persists during a pause, what the reviewer sees, and what happens after approval or rejection. Some OpenAI SDK tool types support programmatic approval callbacks; other approval flows pause for a manual decision. The OpenAI Agents SDK human-in-the-loop guide documents these distinctions.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the implementation story can—and cannot—claim
The available technical documentation establishes that agents can pause for approval, preserve workflow state, and continue after a decision. It does not identify the author’s agent, framework, approval policy, notification setup, or measurements. So it supports explaining how an approval queue can be built, but not claiming that a specific build reduced interruptions, by how much, or that a particular design is proven to interrupt only when it matters.
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