How an AI agent can carry API evidence into assignable remediation work
This workflow gives an AI agent a defined job, a bounded set of records, and a result a person can review. The agent reads the relevant Postman context and matches it with Linear, applies the rules in the prompt, and keeps the source behind every recommendation. It returns a proposed handoff rather than taking consequential actions on its own.
Can an AI agent carry API evidence into assignable remediation work?
Yes. Start with the scope, date range, decision rules, and fields that identify the right records. The agent can collect the evidence, compare states or sources, mark conflicts and missing data, and organize the result around the outcome above. A reviewer then checks the matches and judgment calls before approving messages, record updates, bookings, purchases, publishing, or other write actions. The guide below shows the records, boundaries, prompt, and handoff needed for this specific workflow.
Preserve the reproduction
Postman supplies the request sequence, environment, responses, and test results that reproduce an API problem. Linear supplies issue history, scope, owner, status, and acceptance checks. Combining them prevents a vague “API is broken” report and gives engineering evidence they can rerun.
The agent should search Linear for the endpoint, error signature, client flow, and affected service before drafting a new issue. A possible match should show why it overlaps and where the scope differs. Secrets and full customer payloads stay out of Linear.
Example starter prompt
Use the Postman reproduction [collection and request] to prepare Linear follow-up for team [team].
Summarize the smallest failing sequence, expected and observed responses, safe inputs, environment, and repeatability. Search Linear for related issues and classify matches as direct, partial, or unrelated.
Draft an issue or issue update with acceptance checks, but do not create it or change the Postman collection.Make acceptance checks executable
Each check should name the request, expected status or field behavior, and fixture. Separate the fix from later work such as adding collection coverage or improving error messages.
Questions this workflow answers
How can I turn a reproducible API failure into an issue an engineer can fix without another discovery meeting?
The agent treats the verified request sequence as the technical source and the issue tracker as the work record. It first confirms that the failure repeats in a named test environment with sanitized fixtures. It captures the smallest request order, expected behavior, observed status and fields, relevant headers, variable setup, and the first point of divergence. Credentials, tokens, full user records, and large response bodies never move into the issue.
Before drafting new work, it searches existing issues using endpoint shape, service, error code, response signature, client path, and affected release. A direct match covers the same behavior and environment. A partial match may share the endpoint but involve a different authorization state or payload. The agent explains that relationship so the owner can update, link, or reject the candidate instead of creating a near-duplicate.
The draft issue gives engineering an executable starting point. Acceptance checks name the fixture, request, expected status, required response fields, and relevant negative case. If the fault is uncertain, the issue says “investigate” and defines the evidence needed to finish; it does not present a guessed implementation as the fix. Follow-up work such as better error copy or broader collection coverage stays separate unless it is required to resolve the reported behavior.
The handoff includes the proposed team and owner, sanitized reproduction link, environment, impact statement grounded in known reports, duplicate review, acceptance checks, and open questions. An engineer reviews access and reruns the sequence before accepting scope. Issue creation, assignment, status changes, and edits to the shared Postman collection remain approval-based.
The handoff should link the sanitized Postman example and state which evidence still needs an engineer to verify.
Acceptance criteria can name the exact request order, fixture, expected status, and response fields. If the bug appears only after refreshing a token twice, “endpoint returns 200” is too broad. The issue should require that sequence to pass and a neighboring unauthorized case to remain rejected. Secrets stay in the approved environment, while the ticket records variable names and setup instructions. Another engineer can reproduce the failure without asking the reporter to reconstruct hidden state.