What problem does it solve? Teams adopt AI coding tools unevenly, creating drift, islands, and ungoverned agent usage. This Skill provides a structured 8-stage framework to diagnose where a team or organization sits in AI engineering maturity and plan the next concrete advancement step without skipping foundational stages. ## Core Features & Use Cases - Stage Diagnosis: Maps current AI tooling practices (shared context files, skills, prompts, MCP servers, guardrails) to one of eight maturity stages from vacuum to autonomous factory. - Advancement Planning: Surfaces one concrete recommended next step per session, grounded in governance, shared context, and eval prerequisites. - Governance Alignment: Cross-references security checklists, git workflow guardrails, and cache-first prompts to ensure AI amplifies good practices rather than bad ones. - Use Case: During a standup or planning session, invoke the Skill to assess whether the team is at Stage 2 (individual drift) versus Stage 4 (standardization), and identify the specific gap—such as missing shared prompt libraries or absent PR gates on agent output. ## Quick Start Ask the AI to assess the team's current AI engineering maturity stage and recommend one concrete advancement step using this framework.
