AI incident triage: from customer report to useful handoff
AI incident triage helps a team turn an incomplete problem report into evidence someone can act on. Define its output as an affected scope, a timeline, observed symptoms, and a next owner. A likely explanation can guide investigation, but it should remain a hypothesis until the evidence supports it.
Agree on when to escalate immediately
Before adding an agent, document which reports require the existing incident response process: for example, suspected data exposure, possible data corruption, or a widespread service interruption. A triage assistant must not delay that handoff while it searches for a more complete answer. The incident owner decides how to respond to the impact.
Google’s SRE guidance separates impact assessment and restoring service from deeper troubleshooting. That distinction is useful here: gathering a detailed explanation should support the response, while urgent mitigation remains with the people and procedures responsible for it.
Google SRE: effective troubleshooting and triage
Collect the smallest useful evidence package
Begin with the reporter’s expected behavior and what they observed instead. Resolve the customer, environment, and relevant request or job identifier. Use a bounded time range around the reported failure so a routine investigation does not become an unrestricted search through production data.
- Affected scope: the known customer, job, service, and environment; wider impact remains unknown until checked.
- Timeline: the report time, observed failure time, and last known successful operation, with the timezone stated.
- Evidence: relevant status records and permitted error details, each tied to its source.
- Investigation gaps: unavailable sources, truncated results, stale data, and checks not yet performed.
Keep credentials and unrelated personal information out of the handoff. Check the destination audience before copying source material into a ticket or message. A teammate’s permission to inspect a record does not establish that everyone in a shared channel may read it.
Keep observations and hypotheses separate
Consider a fictional setup job that stopped after a downstream request timed out. “The request timed out at 14:05 UTC” is an observation if the job record says so. “The downstream service was unavailable” is a hypothesis. “The customer’s workspace was not created” needs a separate check in the destination system.
Ask for the evidence that would distinguish possible causes. If the agent cannot access that evidence, include the missing check in the handoff. This gives engineering a specific starting point and keeps a plausible summary from turning into an unsupported root cause.
Treat recovery as a separate decision
Finding a familiar error does not authorize a retry. Check the runbook’s preconditions, confirm the target record, and establish whether the earlier attempt partially succeeded. If the problem is outside the documented case, or the outcome of a prior action is uncertain, stop the recovery path and escalate.
For a known recovery, prepare a specific operation and follow the configured approval rule. A useful approval preview makes the target, environment, inputs, and expected effect visible. After execution, verify the target state before reporting that service has recovered.
What a human approval for an AI agent needs to show
Use a handoff template the next person can continue
- Problem: what the reporter expected and what happened.
- Scope and timeline: verified affected records and relevant timestamps.
- Confirmed findings: source-backed observations, with links or identifiers.
- Open questions: hypotheses and the checks needed to evaluate them.
- Actions attempted: exact operation, approval if required, and observed result.
- Next owner: the team or person responsible for continuing the investigation.
Review the package with an engineer who did not handle the original case. If they need to repeat basic lookups before they can begin, improve the evidence fields. If they mistake a hypothesis for a finding, change the wording and review criteria.
Start with investigation, then evaluate recovery
In GlowForm, this pattern starts with configured connections and published read tools scoped by agent policies. The assistant can help investigate and draft an operation; a person reviews and submits the draft. A monitoring feed, an on-call escalation process, and a recovery procedure must be designed for your environment rather than assumed from the presence of a connector.
Measure the time to a useful handoff, missing evidence, incorrect explanations, and the number of follow-up questions engineering needs. A shorter summary is only an improvement if the next person can make a better decision from it.