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S1 · AI-Native QA & SDET · L2 UNDERSTAND

AI Application Evaluation

Replace 'does the answer feel right?' with criteria, cases and results the team can inspect.

Best for: QA leads and engineers who must judge an AI feature before release and need more than a demo to point to.

$49 one-time · includes L0-L2 of S1 · AI-Native QA & SDET

Get L2 UNDERSTAND for $49 · our storeSee the whole series

Paid purchases: 7-day money-back guarantee and at least six updates a year for five years, as set out in the terms.

What you paid for any lower level of the same series counts toward any higher level (L1 START at $19 makes L4 SCALE cost $130). To claim it, email hello@nobrainer.tech with your receipt (how the credit works).

Need copies for colleagues? Each person gets their own copy; email hello@nobrainer.tech.

S1 · AI-Native QA & SDET L2 UNDERSTAND: AI Application Evaluation, product artwork

You walk away with

  • An evaluation contract, a fixture plan, a result review and an open-risk list, written as JSON and as an HTML report.
  • Deterministic checks, semantic criteria and prohibited outcomes kept apart, each with an owner and pass, fail and unresolved definitions.
  • A CI evaluation gate for GitHub Actions, GitLab CI or make that returns a verdict per critical segment, with two policies (default and exploratory).
  • Editable templates: decision record, RACI (responsible, accountable, consulted, informed), risk register, rubric, review checklist and a stakeholder one-pager.
  • A worked IT-helpdesk example with generated English and Polish reports, a 122-page field guide and 61 automated tests.

What the workflow does

Define the boundary, write acceptance criteria, choose sanitized fixtures, run a reviewable evaluation plan, and record gaps.

Bring

  • feature boundary
  • risk and acceptance criteria
  • sanitized representative fixtures

Leave with

  • evaluation contract
  • fixture plan
  • result review
  • open risk list

What is in the package

Includes L0-L2 of S1 · AI-Native QA & SDET: Failure Evidence Triage Workflow, Test Failure Triage Workflow and AI Application Evaluation.

You need: Node.js 22 and a terminal.

Each package is a working workflow with tested code, a runnable example, recovery steps and an HTML report, plus an English and Polish guidebook that explains the method. The workflow is the product; the guidebook supports it.

Prices are cumulative: each price covers that level and every level below it, so the catalog shows no sums or savings.

What the guidebook covers

  • LLM behavior and complete system versioning
  • deterministic and semantic acceptance criteria
  • fixture cohorts and provenance
  • repeatable evaluations for variable outputs
  • result review and unresolved evidence

The guidebook extends the workflow with the reasoning and adaptation guidance. It is not evidence that a result has already run in your environment.

Use it safely

Use sanitized inputs inside a declared boundary and review every proposed action. The workflow stops when evidence, authority or an owner decision is missing.

The included code runs on your machine, makes no model calls and needs no AI tool. If you want an assistant to help draft the input, the onboarding guide shows how; you review the result before anything is acted on.

Next level

L3 APPLY, AI Test Automation Review, helps you choose which AI-assisted tests are worth writing, propose the smallest change and name who maintains it.

See L3 APPLY: AI Test Automation Review · Open it in our store · See all five levels

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