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S2 · AI Evaluation & Reliability · L2 UNDERSTAND

Non-Deterministic Evaluation Design

Define how much variation is acceptable and compare runs on evidence the team can defend.

Best for: Engineers who own AI quality criteria and regression decisions and are tired of subjective arguments.

$49 one-time · includes L0-L2 of S2 · AI Evaluation & Reliability

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.

S2 · AI Evaluation & Reliability L2 UNDERSTAND: Non-Deterministic Evaluation Design, product artwork

You walk away with

  • An evaluation contract, a comparison plan, an evidence summary and an uncertainty register, as JSON, Markdown and HTML.
  • A contract template, gate policy, decision register, trials template and rubric to fill in with your own system.
  • An evaluation gate for GitHub Actions, GitLab CI, pre-commit or make.
  • A worked helpdesk-triage example with English and Polish reports, a 115-page field guide and 65 automated tests.

What the workflow does

Choose an oracle, define sampling and confidence language, compare observations, and record what remains uncertain.

Bring

  • system behavior definition
  • risk and quality dimensions
  • representative sanitized data

Leave with

  • evaluation contract
  • comparison plan
  • evidence summary
  • uncertainty register

What is in the package

Includes L0-L2 of S2 · AI Evaluation & Reliability: LLM Failure Pattern Scan, Initial LLM Test Checklist and Non-Deterministic Evaluation Design.

You need: Node.js 22 and a terminal. The included L1 folder runs on Python 3.10 or newer.

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

  • why LLMs fail differently
  • system definition and versioning
  • variability and regression design
  • first AI test-suite structure
  • metrics, governance and review

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, Production AI Evaluation System, moves evaluation out of the notebook into a dataset, an evaluator, thresholds, CI and monitoring that owners can act on.

See L3 APPLY: Production AI Evaluation System · Open it in our store · See all five levels

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