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Evaluating AI Systems for Enterprise Deployment

7 chapters · 31 lessons

1. 1. Reading Evaluation Artifacts Like an Engineer

   4 lessons

   Learn to extract actionable insights from system cards, model cards, and evaluation reports by focusing on methodology over results.

2. 2. Translating Claims into Evidence Requirements

   5 lessons

   Build a framework for matching vendor capability claims to the evaluation evidence needed to support deployment decisions.

3. 3. Failure Mode Analysis for Deployment Planning

   4 lessons

   Learn to interpret documented limitations and failure patterns, then design mitigations that fit your operational context.

4. 4. Building Internal Acceptance Criteria

   5 lessons

   Create testable, evidence-based standards for model selection that align with your organization's risk tolerance and use cases.

5. 5. Comparative Model Assessment in Practice

   4 lessons

   Apply structured comparison techniques to evaluate multiple models for the same workload using real system card examples.

6. 6. Operational Controls and Monitoring Design

   5 lessons

   Translate evaluation findings into deployment guardrails, logging strategies, and ongoing monitoring plans.

7. 7. Governance Conversations and Stakeholder Reporting

   4 lessons

   Communicate evaluation findings and deployment recommendations to leadership, legal, and cross-functional teams.