Write the total, gate status, three highest-priority gaps, owner and next evidence required. Keep an explicit “retain current API” outcome. The desk recommends a metadata-only first review: dataset descriptions, cost units and example failure categories normally suffice to identify preparation work without receiving customer records.
What should the result page or internal note contain?
Section source library
This page contains no direct external citations. These are the section’s references; they do not independently validate the desk’s proposed scoring or methods.
- Demystifying evals for AI agents — Anthropic, 9 January 2026 →www.anthropic.com
- Llama 3.3 Community License Agreement — Meta →github.com
- AI Risk Management Framework — NIST →www.nist.gov
- RouteLLM: Learning to Route LLMs with Preference Data — Ong et al., revision 23 February 2025 →arxiv.org
- A Field Guide to Rapidly Improving AI Products — Hamel Husain →hamel.dev
- GroupKFold — scikit-learn documentation →scikit-learn.org
- Pricing — Together AI, snapshot checked 26 October 2026 →www.together.ai
- The Inference Engineering Masterclass — Philip Kiely and Ali Taha, Latent Space, 3 August 2026 →latent.space
- The Open Source AI Definition 1.0 — Open Source Initiative →opensource.org
- SB26-189 Automated Decision-Making Technology — Colorado General Assembly →leg.colorado.gov
- Guidance on HIPAA & Cloud Computing — HHS Office for Civil Rights →www.hhs.gov