Free workflow walkthrough

An AI-assisted bug triage workflow that does not invent a diagnosis

AI is useful in bug work when it helps structure evidence, compare hypotheses, and keep the fix narrow. It becomes risky when a plausible story is presented as a root cause before the failure is reproduced or the relevant code path is inspected.

An AI-assisted bug triage workflow that does not invent a diagnosis evidence-boundary preview

01 / Scenario

Start with the boundary, not the model.

Imagine that patients can double-book a physical slot near the spring daylight-saving transition, but only on reschedule in Europe/Bucharest. A useful triage process preserves that narrow scope until evidence proves otherwise. It does not rewrite scheduling rules for every timezone because the symptom sounds temporal.

Evidence rule

An AI assistant may organize supplied facts, suggest questions, and draft a bounded artifact. It cannot turn an unverified claim into repository evidence, stakeholder approval, a test result, or production truth.

02 / Workflow

A repeatable sequence.

  1. 01

    Make the report actionable

    Capture build, environment, user path, expected behavior, actual behavior, frequency, impact, and existing evidence. Separate what the reporter observed from what the team assumes.

  2. 02

    Reproduce—or bound non-reproduction

    Record exact setup, inputs, timestamps, versions, and outputs. If it does not reproduce, return the matrix you tried and the missing signal needed next instead of declaring the issue invalid.

  3. 03

    Compare the failing path with a control

    A nearby working path often narrows the search faster than reading the whole system. In the timezone example, new booking already normalizes through the scheduling authority while reschedule does not.

  4. 04

    State the smallest supported cause

    Name the condition, the mechanism, and the evidence that connects them. List plausible alternatives that were ruled out and those not yet tested.

  5. 05

    Design the minimal repair

    Correct the cause at the existing authority boundary. Preserve unrelated policy and avoid opportunistic cleanup unless it is required for safety.

  6. 06

    Protect the invariant

    Write a regression that fails for the original defect, control tests for adjacent behavior, and rollout/rollback checks appropriate to the risk.

03 / Fictional worked excerpt

What a bounded output looks like.

The table below condenses a fictional example included for demonstration. It is not a customer result, production test, approval, or performance claim.

Failing path

Reschedule compares a naive local value with stored UTC instants

Working control

New booking already uses timezone-aware normalization

Repair boundary

Route reschedule through the existing normalization function

Still unknown

Other timezones and historical overlaps require separate verification

04 / Failure modes

Where otherwise plausible AI output goes wrong.

  • Diagnosing from the ticket title
  • Changing global restrictions to make one reproduction pass
  • Writing a test that mirrors the implementation instead of the invariant
  • Claiming production repair from a local or fictional example

05 / Read-only checklist

Use this before calling the artifact complete.

  • Exact environment and build
  • Expected and actual behavior
  • Reproduction log or bounded non-reproduction
  • Working control path
  • Cause, mechanism, and supporting evidence
  • Minimal repair boundary
  • Regression plus control cases
  • Rollout signal and recovery path

This checklist is intentionally read-only: it helps you inspect a workflow without exposing the full native skill files, portable prompts, templates, or the bundle-exclusive orchestration skill.

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Questions

Using AI without hiding uncertainty.

What should AI do during bug triage?

It can structure the report, propose a reproduction matrix, compare evidence, generate bounded hypotheses, and help draft regression cases. It should not claim a root cause or test result it has not observed.

What is a minimal fix?

A repair that corrects the evidence-supported cause with the smallest reasonable regression surface. Minimal does not mean skipping tests, rollout controls, or required safety work.