Blog Series

The Resourceful AI Skill — 3 Posts on What Makes an AI Skill Production-Ready

A practitioner series on AI skill quality: a maturity model, an engineering contract with behavioral and capability boundaries, and a measurement notebook showing the before/after delta on a real published skill.

3 posts · For AI engineers, platform engineers, and technical leads building or deploying AI skills
  1. 1
    How Resourceful Is Your AI Skill? AI skill maturity explained: a four-level model and three real gaps found in a published skill — token cost, security surface, and behavioral testing. AI engineers, platform engineers, and technical leads building or consuming AI skills in production workflows
  2. 2
    The AI Skill Engineering Contract AI skill engineering contracts explained: behavioral boundaries, capability manifests, resource budgets, and the rule about model-enforced security. AI engineers, platform engineers, and technical leads building or deploying AI skills in production agent workflows
  3. 3
    Measuring What 'Resourceful' Actually Means Measure AI skill quality with a Colab notebook: token cost, security surface, and regression testing — before and after applying an engineering contract. AI engineers, platform engineers, and technical leads building or deploying AI skills in production agent workflows