Show HN: I Built an AI Maturity Model for Software Engineers (and No One Cared)
3 days ago
- #AI Maturity
- #Software Engineering
- #Responsible AI
- AI is increasingly embedded in mainstream development, but many teams lack governance frameworks and skill alignment.
- The AI Maturity Model for Software Engineering Teams (AI-MM SET) helps assess and evolve AI adoption.
- The model is structured as a three-axis matrix with five maturity levels, six core dimensions, and role-based progression.
- Maturity levels range from Exploratory (Level 1) to Transformational (Level 5), showing increasing sophistication and impact of AI.
- Six core dimensions include AI Literacy, Workflow Integration, Tooling Integration, Trust & Governance, Collaboration, and Business Impact.
- Role-based progression outlines expectations from Junior Engineer to Distinguished Engineer.
- The model provides a roadmap for responsible AI adoption, managing risks, and realizing measurable value.
- Teams can use the model for assessments, benchmarking, planning, and aligning AI practices with business goals.
- The AI-MM SET is open-source and licensed under CC BY 4.0, encouraging contributions and adaptations.