4 items across 1 sections
Design and template for long-form operational case studies — evidence standards, timeline structure, outcome measurement, before/after analysis, and the components that make case studies high-authority proof.
Naming conventions, metadata structure, storage organization, integration patterns, and quality standards for operational evidence on AI Execution Lab.
Metadata standards, evidence tagging, retrieval relationships, and operational relevance scoring for the AI Execution Lab evidence archive.
Design specification for the evidence layer — how screenshots, deployment logs, command histories, debugging records, and operational timelines integrate into tracks, failures, playbooks, case studies, and labs.