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Verify an AI agent’s discovery as a set of claims, not as a finished answer. Freeze any proposed action, split the result into facts, calculations, assumptions, interpretations and actions, then open the underlying sources and check that they really support each material claim. Corroborate consequential facts with an independent primary or official source, inspect retrieved content for prompt injection, and validate the proposed action’s target, scope, permissions and reversibility. A person should approve high-impact, destructive, externally visible or irreversible actions before execution. Execute only the approved scope with least privilege, keep an audit record, and review the outcome afterward. Fluent wording or a confidence score is never a substitute for evidence.
What should I do when an AI agent proposes an action?
Freeze the action immediately. Treat the agent’s discovery as a lead or recommendation until a person has reviewed the evidence and approved the exact operation.
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- Pause tool execution, queues and scheduled follow-ups that depend on the discovery.
- Save the original response, cited links, retrieved documents, tool calls and timestamps.
- Identify whether the proposed result could expose data, spend money, change access, affect a person, damage a system or create an external commitment.
- Assign a named reviewer and define what evidence is required before the action can proceed.
Freezing is not a rejection. It is a separation between finding something and deciding what to do about it, which prevents an unverified intermediate result from gaining authority through automation.
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How do I turn an agent’s discovery into claims I can check?
Break the response into small statements and label what kind of statement each one is. A single paragraph often mixes evidence with arithmetic, assumptions and a recommended action.
Facts
Facts are externally checkable statements, such as a product’s current limit, a regulation’s effective date or the status of an incident. Record the exact wording, source, publication date, owner and relevant geography or version.
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Recalculate totals, rates, conversions and forecasts independently. Preserve the inputs and formula rather than accepting a rounded number. A correct formula applied to stale or mismatched inputs still produces a misleading result.
Assumptions
Mark conditions the agent supplied without proof: an exchange rate, a user’s identity, an assumed renewal date, a default permission or an interpretation of an ambiguous requirement. Ask whether each assumption is authorized and whether changing it would change the decision.
Interpretations
Separate what a source says from what the agent infers. Interpretations should identify the passage they rely on and acknowledge reasonable alternatives where the wording is uncertain.
Proposed actions
Write the recommendation as an explicit operation: who or what is affected, which resource is targeted, what will change, which permissions are needed, whether the operation can be reversed and who must approve it. Mark claims that are material to the decision; verify those first and most rigorously.
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Open every material citation yourself. NIST’s Generative AI Profile calls for reviewing and verifying sources and citations in generative-AI outputs during pre-deployment risk measurement and ongoing monitoring.
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- Confirm that the source exists. Follow the citation to the original page, document or dataset. A title that looks plausible is not evidence that the cited material exists.
- Read the supporting passage. Check whether it states the agent’s claim, supports only a narrower point, or contradicts it. Watch for a citation attached to a whole paragraph when it supports only one sentence.
- Check date and version. Note publication, update and effective dates, plus the software, policy or document version. Prefer the version that applied when the event or decision occurred.
- Check jurisdiction and scope. A rule for one country, industry, account type or deployment edition may not apply to yours. Record exclusions and definitions that limit the claim.
- Assess authority and independence. For a legal, safety, security or financial decision, prefer an accountable official or primary source. A page that merely repeats the agent’s wording is not independent corroboration.
- Capture the evidence. Store the relevant passage, link, access time and any caveat alongside the claim so another reviewer can reproduce the check.
Do not infer support from a citation’s presence, domain name or polished formatting. The evidence must match the exact proposition and the conditions under which you intend to use it.
How many sources should I check for an important claim?
There is no universal source count. Critical claims deserve independent corroboration, and the required effort should rise with the harm and irreversibility of being wrong.
The Canadian Centre for Cyber Security recommends validating critical aspects against multiple sources and using redundant validation. “Multiple” means genuinely independent evidence, not several pages copied from the same announcement. For a routine, reversible lookup, one authoritative source may be enough; for a destructive or externally consequential decision, obtain an independent primary or official confirmation and have a person review the conflict points.
- Low consequence: Verify the claim against the most authoritative available source and test the resulting operation in a reversible way.
- Material consequence: Add an independent source with a different owner or data path, and document why the sources are appropriate.
- High consequence or disagreement: Preserve both versions, identify the precise conflict, and escalate to a qualified human rather than silently selecting the more convenient answer.
Source independence is about origin, not URL count. Two articles quoting the same press release provide one underlying assertion. Conversely, an official record and an independently maintained technical record may provide useful redundancy even when they describe the same event.
How can I catch prompt injection in webpages, documents and tool responses?
Handle all external content as data, never as instructions with authority over the agent. The Canadian guidance warns that embedded directions in untrusted content may be prompt injection; the UK National Cyber Security Centre says prompting alone is not enough and should be combined with technical and operational controls.
Signs to look for
- A page tells the agent to ignore its task, change its rules or treat the page as a system message.
- A document asks for passwords, tokens, private files or broader permissions than the stated job requires.
- Content urges the agent to skip citations, suppress uncertainty, hide a warning or bypass a human approval step.
- A tool response requests an unrelated network call, file upload, payment or destructive command.
- Instructions appear in hidden text, comments, metadata, attachments or unusually encoded strings rather than in the document’s substantive content.
Safe handling procedure
- Keep the agent’s task and authorization outside the retrieved content in a separate, higher-trust control layer.
- Quote or summarize suspicious instructions as evidence for the reviewer; do not execute them.
- Ask whether the requested permission, destination and side effect are necessary for the approved task.
- Require a fresh human decision before changing scope, secrets, tools or approval status.
- Record the injection attempt and the control that blocked it, then test whether similar content can trigger the same behavior.
Prompt injection can be present even when the underlying factual content is accurate. Verify the facts and the authority of every instruction separately.
How should I validate the proposed action before execution?
Validate the action as structured data, not as free-form prose. OWASP recommends validating outputs before execution and separating decision-making from execution for high-impact actions.
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| Field to validate | Reviewer’s question |
|---|---|
| Action | What exact operation will occur? |
| Target | Which account, record, system, recipient or dataset is affected? |
| Scope | What is explicitly included, and what is excluded? |
| Permissions | Are the requested credentials and capabilities the minimum necessary? |
| Reversibility | Can the result be rolled back, and is the rollback documented and tested? |
| Approval status | Who approved this exact action, under which policy and at what time? |
| Expected result | What observable outcome will show that execution succeeded? |
Reject or return an action for clarification when any field is ambiguous. “Clean up the account” is not an executable scope; a list of record identifiers, operation types and exclusions is. A validated schema also prevents an agent from smuggling a new destination or permission into an otherwise approved request.
When is human approval required?
Put a human checkpoint before any high-impact, destructive, externally visible or irreversible action. The reviewer should approve the exact target and scope after checking the evidence, not approve a general intention that the agent can later expand.
High-impact actions
Require approval when the result can materially affect a person’s rights, safety, finances, employment, access or legal position. The reviewer should be competent to assess both the evidence and the consequences.
Destructive actions
Deletion, overwriting, revocation or publication should remain paused until the evidence and recovery path are confirmed. A backup is not the same as a tested rollback; verify that the intended data can actually be restored.
Externally visible actions
Messages to customers, regulators, partners or the public create commitments that an internal draft does not. Review recipients, wording, attachments, disclosures and timing separately from the factual discovery that prompted the message.
Irreversible actions
If the effect cannot be undone, treat approval as mandatory even when the agent’s confidence is high. Record the approver, evidence reviewed, decision time and any conditions attached to the approval.
Lower-risk automation is possible only when the operation is narrowly scoped, reversible, permission-limited and covered by a policy that specifies when to pause for a person.
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How should I approve, execute and log a verified action?
Approve only the action that was checked, execute it with least privilege, and create an audit record another person can understand.
- Assemble the review packet. Include the claim list, source passages, dates, jurisdiction, calculations, assumptions, conflicts, proposed action schema and injection findings.
- Obtain explicit approval. Record the reviewer, timestamp, approved target, scope, permissions, reversibility conditions and any limits on timing or volume.
- Constrain execution. Use the smallest credential, rate limit, dataset and time window that can complete the approved operation. Keep an external pause or disable mechanism available.
- Prevent scope drift. If the agent asks for a new tool, recipient, permission or target, stop and send the change back through review.
- Log the event. Preserve the discovery, evidence, tool calls, approver, execution parameters, result and errors in a human-readable record.
- Confirm the result. Check the actual outcome against the expected result before declaring the task complete.
Logging is part of verification, not clerical cleanup. Without the original evidence and approval context, a later reviewer cannot tell whether a failure came from a bad discovery, an unauthorized change or an execution error.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should I review after the action runs?
Compare the observed result with the expected result and look for anomalies, drift or side effects. Verification continues after execution because tools, data sources and permissions can change.
- Confirm that only the approved target and scope changed.
- Check downstream records, notifications and access controls for unintended effects.
- Investigate missing, duplicated, delayed or unusually large results rather than treating them as normal variance.
- Record whether the source, tool, model, permission set or operating environment differed from the one reviewed.
- Reassess the workflow when tools, data sources, permissions or scope change, and after adversarial tests reveal a weakness.
The Canadian, UK and OWASP guidance all point toward ongoing monitoring and the ability to pause or disable behavior when it becomes unexpected. A workflow that is safe for one version or dataset may require a new review after an update.
What should I do when verification fails?
Stop the proposed action, preserve the evidence and narrow the agent’s authority. Ask for a primary source or qualified human review instead of allowing the agent to fill the gap with a guess.
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- Pause execution and disable the relevant automation if behavior is unexpected.
- Preserve the original output, retrieved content, source versions, tool calls and audit trail.
- List the failed checks: unsupported citation, stale date, jurisdiction mismatch, unresolved conflict, injection attempt or invalid action field.
- Request the missing primary evidence or route the decision to an appropriate human owner.
- Reduce permissions, target scope and rate limits before any retest.
- Document the disposition: rejected, corrected, escalated or approved with conditions.
If the action already occurred, use the documented rollback or recovery path, compare the actual state with the intended state and investigate the discrepancy. Do not overwrite the record of the original error; it is needed to understand and prevent recurrence.
How do I choose a verification design for a particular task?
Choose controls according to the harm of an error and the amount of uncertainty, not according to how polished the agent’s answer sounds.
| Decision factor | Questions to answer before choosing controls |
|---|---|
| Impact and reversibility | What happens if the claim is wrong, and can the effect be undone? |
| Evidence quality | Is the source primary or official, current, jurisdictionally relevant and sufficiently detailed? |
| Independence of checking | Will a human, a second system or a redundant source challenge the first result? |
| Permission scope | Can the task run with fewer capabilities, fewer records or a narrower target? |
| Auditability | Are claims, evidence, tool calls, approval and outcome recorded for later review? |
| Latency and cost | How much review time is justified by the consequence of being wrong? |
| Pause and rollback | Can an operator stop the process and restore the prior state? |
For a low-impact lookup, the design may be a source check and a reversible test. For a consequential decision, combine independent corroboration, structured action validation, human approval, least privilege, logging and post-execution monitoring. The design should make unsafe escalation harder than safe stopping.
What does a complete verification checklist look like?
Use this checklist at the approval gate:
- The action is frozen until review is complete.
- Facts, calculations, assumptions, interpretations and proposed actions are separated.
- Material claims are identified and each citation is opened.
- Sources support the exact claims and match the relevant date, version, jurisdiction and scope.
- Consequential claims have independent corroboration.
- Conflicts are recorded and escalated, not silently resolved.
- Retrieved content was inspected for prompt injection and did not change the agent’s authority.
- The action schema specifies operation, target, scope, permissions, reversibility, approval and expected result.
- A person approved high-impact, destructive, externally visible or irreversible work.
- Execution uses least privilege, rate limits and an external pause or disable control.
- The evidence, approval, tool calls, result and errors are logged.
- The outcome was compared with expectations and the workflow was reassessed after relevant changes.
This process does not require distrusting every automated discovery. It ensures that trust is earned by evidence, bounded permissions and accountable decisions rather than by fluent prose.
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Can an AI agent’s confidence score replace source verification?
No. A confidence score describes the system’s internal assessment, not whether a citation exists, is current or supports the claim. Use it to prioritize review at most; the underlying evidence and decision controls still determine whether an action is safe.
What makes a second source genuinely independent?
Its facts should come from a different owner, record or collection process rather than copying the first report. Several pages repeating one announcement add visibility but not independent corroboration.
Do reversible, low-risk tasks need a person every time?
Not necessarily. A policy can permit narrowly scoped automation when the operation is reversible, permission-limited and monitored, with a clear pause condition. Any expansion of target, scope or permissions should return to human review.
When should an agent workflow be reassessed?
Reassess it when tools, data sources, permissions or task scope change, and after monitoring finds drift or an adversarial case. A previously acceptable control design may no longer match the new environment.
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