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Controlled AI QA System

Introduce AI where it helps, but keep structure, review, and validation in front of speed. This path is for teams that want acceleration without hype or blind trust.

What this path is

AI assists with planning, locator suggestions, and draft asset creation, but the system still enforces deterministic execution and validation. The result is faster movement without giving up control.

Walkthrough structure

  1. Capability mapping and trust assessment
  2. AI-assisted planning and locator suggestions
  3. Validation pass on assumptions and structure
  4. Controlled test construction
  5. Deterministic execution and observation

What you get

  • AI-assisted test planning
  • Validated locator suggestions
  • Drafted page objects and specs
  • Repeatable execution pipeline
  • Structured artifacts when failures matter

Trust-based entry points

Low trust

AI should not be the first move here. Stabilize the signal first.

  • Start with anti-pattern validation
  • Sprint 3–5 first
  • Introduce AI only after determinism improves

Medium trust

The best entry point for controlled AI adoption.

  • AI-assisted planning and locators
  • Sprint 5 — Test Data and State Reset
  • Sprint 6 — Time-to-Signal and Release Gates
  • Sprint 14–15 when artifact structure is needed

High trust

Expand AI support into page objects and specs while keeping review and gates.

  • Sprint 8 — Page Object Architecture at Scale
  • Sprint 14–17 for validation and release control

Who this is for