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AI Agent Writes: Drafts, Approval Gates, and Audit Logs

Drafts, approval gates, permissions, and audit logs control different stages of an AI agent’s write. Learn what each does and how to choose by impact and reversibility.
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To stop an AI agent from making an unapproved change, control the write before it happens: keep work in a draft, require approval for selected actions, or remove write capability. Audit logs help explain what happened afterward, but they do not prevent a write or prove it was approved. These controls address different stages, so the right setup depends on the action’s impact, who authorizes it, the agent’s access, and what records you need.

How the three controls differ

Pattern When it acts What it does Question to check
Draft first Before external commitment Lets the agent prepare content without sending, submitting, deleting, or updating external state. Can the draft escape or trigger a downstream action?
Approval gate Immediately before a selected write runs Pauses execution for a person or policy decision. Who approves this exact action and its parameters?
Restrict and audit Restriction acts before execution; audit records events afterward Limits available operations or scope, then retains evidence for review. Which writes are unavailable, and what can an administrator reconstruct later?

A draft, an approval prompt, a permission boundary, and an audit event are not interchangeable. A draft limits commitment; an approval gate adds a decision point; permissions constrain capability; and a log supports investigation. For a high-impact action, more than one layer may be appropriate.

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Draft first: let the agent prepare, not commit

A draft-first setup is useful when an agent can do valuable work—such as composing a message or preparing an update—but a person should decide whether it reaches recipients or another system. Microsoft’s access patterns and controls guidance recommends allowing draft creation without external side effects, while treating send, submit, delete, and update as actions that should receive policy checks and often explicit user approval.

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This is an execution boundary, not a promise that every connector has a native draft state. Check the specific action and connector: does the draft remain isolated until a person or a separate tool commits it, or can creating it itself notify recipients or trigger a workflow? If the task needs only reading, drafting, or recommending, withholding write access altogether is also a valid choice.

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Approval gates: pause before a selected write

An approval gate lets an agent reach a write action but pauses it for authorization. OpenAI’s Workspace Agents documentation says app and connector write actions default to “Always ask” during an agent run. Depending on the app, builders may set a write action to “Never ask” or use a custom approval setting. The documentation advises care with write approvals in workflows that send, edit, post, or delete content.

Approval behavior is only one layer of access. OpenAI’s admin guidance for plugins and apps separates role access (who can use an app), Actions (what it can do), and Permissions (when ChatGPT asks before using it). Provider approval, OAuth scopes, and ChatGPT action settings are distinct checks: granting an OAuth scope alone does not enable an action. Availability varies by app. Disabling new actions applies to actions introduced later; it does not turn off actions already enabled.

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Microsoft’s implementation guidance recommends policy checks before tool execution that consider the user, tenant, agent, tool, target resource, permissions, and whether approval is needed. It distinguishes draft creation from send, submit, delete, or update. Calls that change permissions or infrastructure warrant a privileged workflow, audit logging, and human review.

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Restrict writes and preserve evidence

Limit what the agent can do

“Don’t” can mean removing write actions entirely or allowing only specific operations against narrowly scoped resources. Microsoft’s guidance on granting agents access to Microsoft 365 resources describes delegated permissions, where an interactive agent acts on behalf of a signed-in user, and application permissions, where an autonomous agent operates without a user present. These are different operating contexts; the identity and scope determine whose resources the agent can affect. Microsoft also describes access packages with grants that can expire or be revoked, and recommends narrow resource scopes where possible.

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Verify the actual enabled actions and permissions rather than relying on an agent’s natural-language instructions to refrain from writing. A promise in a prompt is not the same as an enforced capability limit.

Use audit records to investigate, not to prevent

GitHub’s agentic audit event documentation identifies fields such as the action performed, whether the actor is an AI agent, an agent session identifier when an event results from a session, and the user who initiated it. GitHub separately documents streamed Copilot API usage records with a timestamp and event ID, among other fields. That streamed feature is in public preview and is documented as available to enterprises using Enterprise Managed Users and GitHub Enterprise Cloud enterprises with data residency; it is not a universal GitHub audit feature.

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Microsoft 365 admin center documentation describes separate Data & tools, Permissions, Security, and Activity views. Tool listings can include actions that write data and merit closer review; surfaced metadata varies by agent type and platform. The Security tab has licensing conditions in the documented experience, so not every administrator will see every panel.

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Make actions visible to people

Technical records are not the only useful evidence. Slack’s agent design guidance says identity-based actions should be visible and reviewable. It recommends labeling actions as being “on behalf of” a user, visibly identifying autonomous content that has not been reviewed, and providing a review surface—especially for asynchronous or bulk actions.

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Choose controls by impact and reversibility

Match the control to what can go wrong. Editing an internal work note is not equivalent to sending an external message, deleting a record, changing permissions, or provisioning infrastructure. Consider how broad the target is, whether the change is reversible, and whether a delay for review is acceptable.

  • Low-impact preparation: allow reading and drafting, while keeping drafts isolated from external effects.
  • Meaningful but reviewable changes: enable only the necessary write actions and require approval immediately before execution.
  • High-impact or hard-to-reverse operations: narrow the identity and resource scope, use a privileged workflow with policy checks and human review, and retain audit evidence.
  • Tasks that do not need writes: disable write capability rather than trusting instructions to avoid it.

Then verify the end-to-end path: which identity acts, which resources it can reach, what action is enabled, whether an approval can be bypassed through another route, and what information the resulting record captures. Platform documentation describes available controls and guidance; it does not establish that a control will be effective in every deployment.

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