Sprint / 02 · AI-enabled systems

AI Evaluation and Test Harness Sprint

Evaluate an AI workflow against agreed criteria using a test harness: repeatable checks that show where it performs well and where it fails.

  1. 01Scope
  2. 02Investigate
  3. 03Review
  4. 04Handoff

How evidence is built

From the initial question to the handoff.

A convincing demonstration does not establish performance across the cases, failures, and operating conditions that matter.

  1. 01

    Define intended use and failure

    Turn the AI workflow, operating conditions, and consequential failure modes into measurable evaluation criteria.

  2. 02

    Build a repeatable harness

    Create controlled fixtures, baseline comparisons, and executable checks that can be rerun after changes.

  3. 03

    Report readiness and limits

    Analyze errors and record where the evidence supports proceeding, where revision is required, and what remains untested.

Included work

One intended use. An executable evaluation.

  • Intended use, failure modes, and acceptance criteria
  • Evaluation data or fixtures and a repeatable harness
  • Baseline comparisons and error analysis
  • Traceable results, limitations, and deployment boundary

What you receive

Repeatable tests and readiness findings.

  • An executable evaluation harness
  • Baseline and failure-mode results
  • A reproducible evidence summary
  • A proceed, revise, or stop recommendation

Engagement fit

The decision this Sprint informs.

Whether the AI-enabled system meets defined criteria for its intended use—and where it fails.

Best for
  • Product, engineering, or risk leaders preparing an AI workflow for its next environment
  • Teams that need a reusable regression harness instead of a one-time demonstration
  • Decision owners comparing a model, agent, prompt, or workflow against a baseline
What we need from your team
  • An AI model, agent, or workflow has a defined intended use
  • Representative test cases can be approved for evaluation
  • A decision owner can define acceptable performance
Not designed for
  • General AI strategy or ideation without a system and decision to evaluate
  • Claims of universal safety, fairness, compliance, or readiness
  • Production monitoring across operating conditions outside the agreed test boundary

5–10 business days

Bring the AI workflow and the failure modes that matter.

Discuss this Sprint