Make human approval mean something.

Choose the decision that needs a person

Start with the consequence of the action. Reading an approved document, preparing a draft, changing a customer record, and sending a customer commitment are different permissions. Write a rule for each operation. Do not give the entire workflow one autonomy setting and hope the model uses it sensibly.

For a hypothetical quote-intake workflow, AI could extract the request and flag missing specifications. An approved pricing process supplies the numbers. A reviewer checks the exact quote, recipient, and assumptions before release. Approval to prepare a draft does not authorize sending it; approval to send one quote does not authorize a revised price or another recipient.

Give the reviewer enough information to decide

“The agent wants to continue” is not a useful decision. The review screen should show the proposed action, destination, exact content or before-and-after values, supporting records, unresolved questions, and the consequence of approval. Put the risky change where the reviewer can see it without opening a chain of hidden details.

Offer distinct outcomes: approve this version, reject, request changes, or escalate. If the reviewer edits the proposal, present the resulting version for approval under the agreed rule. Avoid broad batch approvals that hide a different recipient, exceptional amount, or missing source inside otherwise routine requests.

Bind approval to the action that will execute

Ask the implementation partner how the execution step verifies the approval. A record should identify the request, proposal version, destination, permitted operation, reviewer, decision time, and expiry rule. Immediately before execution, check that the reviewer still has authority and that the relevant record or proposal has not changed.

The approval check belongs in the application path that performs the change. A prompt telling the AI to ask first is not sufficient enforcement. Reusing an old approval, opening a direct action endpoint, or calling another tool must not bypass the same boundary. Keep secrets and unnecessary customer details out of the approval record.

Plan for pauses, restarts, and unanswered requests

The workflow needs explicit pending, rejected, expired, and completed states. Assign a review owner and backup, agree a response target, and decide when to escalate. No response should leave a gated action unexecuted. An expired request can be regenerated or reviewed again; it should not acquire permission because the queue is busy.

LangGraph’s official interrupt documentation illustrates a technical pause-and-resume mechanism: execution can wait for external input with persisted state. It also explains that the interrupted node restarts when resumed, so code before the interruption can run again. Buyers should ask where side effects occur and how replay is handled. The mechanism alone does not define your reviewer permissions, expiry policy, or business approval rules.

After approval, a destination service can still fail or return an uncertain result. Require the workflow to reconcile whether the action happened before retrying it. An approval record proves a decision was made; a separate execution result proves what actually happened. Test repeated clicks and restarts so one approved operation does not become two sends or two updates.

Build on governance, then test the actual gate

DBAI’s published governance framework describes scope, role-based access, human review, logging, and a named release owner. This guide turns the human-review control into questions a buyer can put into a workflow brief. It does not claim a certification or report acceptance results for the hypothetical quote example.

Copy this approval brief

# Human approval — one operation
Business operation and consequence:
Actions allowed before review:
Exact action requiring approval:
Actions excluded entirely:

## Review
Primary reviewer / authorized backup:
What the reviewer sees:
Source evidence and unresolved questions:
Approve / reject / edit / escalate behavior:
Response target and escalation owner:

## Enforcement
Request ID and proposal version:
Destination and permitted operation:
Reviewer identity and authorization check:
Changes that invalidate approval:
Expiry and permission-revocation rules:
Execution-time revalidation:
Duplicate-click and restart handling:
Uncertain-result reconciliation:

## Demonstrate before release
Approved version executes once:
Rejected request never executes:
No response leaves action pending:
Price, content, or recipient changes invalidate approval:
Expired or unauthorized approval is refused:
Direct or alternate action path cannot bypass review:
Restart and repeated clicks do not duplicate the action:
Log links decision to verified execution result:

Make review sustainable

A gate that overwhelms the reviewer will eventually become a rubber stamp. During the pilot, measure time spent reviewing, the age of pending requests, edits, rejections, and escalations. Use those observations to improve the input and review screen before changing the authority boundary.

Reduce unnecessary review only through an explicit scope decision supported by observed behavior. Keep consequential actions under the control their risk warrants. The goal is a workflow your team can operate with clear responsibility, not the highest possible percentage of autonomous runs.