AI-guided implementation QA

Start with the symptom.
Leave with evidence.

Give the QA agent a page and a question. The workspace connects runtime behavior, analytics payloads, implementation rules, and a precise next action.

Runtime signals Decoded payloads Launch rules Assurance escalation
New QA mission

What should we investigate?

Draft

Use a public test URL for the isolated remote browser.

Screenshots and supporting files

Drop evidence here, choose files, or paste screenshots copied from Jira.

Drop files here, select +, or paste a screenshot. Up to 10 files · 10 MB each · 25 MB total.

Attachments are added to this QA session’s AI context when the session starts.

Mission details stay in this tab. Attached files are queued for this session’s AI context.
Prompt starters

Begin with a real symptom

Choose an example, then make it specific to your page and implementation.

Designed investigation path

One question, one evidence chain

The remote sandbox follows this evidence path while keeping every manual handoff clear and recoverable.

  1. 01 · ObserveOpen the page and establish runtime scope

    Verify the active property, environment, page state, and visible user journey before interpreting any signal.

  2. 02 · CorrelateMatch rule fires to decoded payloads

    Trace the expected variable through Debug output, network evidence, and the exact request that should contain it.

  3. 03 · ExplainInspect Launch configuration safely

    Compare Published and Latest, review rule scope and components, and identify conflicts without mutating production.

  4. 04 · CollaborateAsk for one precise manual action

    If the behavior needs a human gesture or protected journey, preserve the run and explain exactly what to click and why.

  5. 05 · EscalateUse Assurance only when evidence still conflicts

    Create an explicit session and continue the same evidence chain when local Debug and payload inspection are not enough.