Most AI training teaches you to use the tools. This is the work that determines what the tools can actually do for you.
There are fifteen human competencies that govern the quality of every AI interaction you will ever have. Most of them are never mentioned in any AI course, platform, or tutorial. They cannot be learned by prompting. And they compound — in whichever direction you develop them — across the arc of your entire working life.
This is the framework.
THE PROBLEM WITH HOW AI IS TAUGHT
AI training is overwhelmingly tool-focused. Learn the platform. Learn the prompt patterns. Learn the workflow.
What it consistently omits: the human side of the collaboration.
Your ability to evaluate AI output depends on how well you know what you're evaluating. Your ability to maintain creative authority depends on whether you've developed the capacity to hold vision under execution pressure. Your ability to prevent gradual capability loss depends on whether you have a calibrated, practiced habit of asking what you are delegating and what the long-term consequence is.
None of those are tool skills. They are human skills. Specifically, they are competencies — combinations of knowledge, judgment, habit, and disposition that develop through deliberate practice over time.
This framework maps all fifteen.
THE FRAMEWORK
The fifteen AI competencies are derived from published research in cognitive development, AI literacy, trust calibration, and human factors — including the UNESCO AI Competency Framework, the OECD AI Literacy Framework, the Cattell-Horn-Carroll model of cognitive abilities, and the Lee & See foundational research on human-automation trust.
They are organized in eight developmental stages — from the foundations that make every other competency possible, to the integration-level mastery that governs how everything compounds.
THE EIGHT STAGES
Stage 1 — Orientation: The dispositions and character traits that make every other competency sustainable under pressure.
Stage 2 — Epistemic Grounding: Evaluating the quality of knowledge — yours and AI's — before anything else begins.
Stage 3 — Basic Interaction: The interface between your thinking and AI's execution.
Stage 4 — Quality Control: Judgment, ethics, and the decisions AI cannot reliably make.
Stage 5 — Sustainable Practice: The workflow architecture and deliberate practice design that make improvement compound.
Stage 6 — Creative and Relational Extension: Maintaining authorship and multiplying capability through others.
Stage 7 — Cognitive Deepening: The meta-awareness, systems thinking, and cognitive architecture that only become visible with experience.
Stage 8 — Integration Mastery: The governing meta-skill — active, ongoing calibration of where human judgment leads and where AI carries.
THE FIFTEEN AI COMPETENCIES
Stage 1
- Psychological Foundations and Dispositional Health — The character beneath the skills: the orientations that make all others sustainable under pressure.
Stage 2
- AI-Integrated Psychology of Longevity — What changes when your planning horizon extends by decades and AI becomes the tool for navigating it.
- Epistemic Cognition — Evaluating knowledge quality; maintaining intellectual authority in the human-AI loop.
Stage 3
- Trust Calibration — Appropriate reliance: neither over-trusting nor under-trusting AI.
- Language and Intent Architecture — The interface between your thinking and AI's execution.
Stage 4
- Metacognitive Awareness — Monitoring how you are thinking while AI is doing some of the thinking.
- Judgment and Decision-Making — The decisions AI cannot make and cannot reliably simulate.
- Ethical Reasoning and Principled Navigation — Knowing when AI should not be used, and building principled frameworks for that decision.
Stage 5
- Process and Workflow Architecture — Designing the systems within which AI collaboration happens.
- Deliberate Practice Architecture — Using AI as a development environment, not just a production tool.
Stage 6
- Creative Direction and Authorship — Maintaining creative authority when AI handles execution.
- Social and Relational Competencies — The human-facing dimension of AI collaboration proficiency.
Stage 7
- Higher-Order Cognitive Skills — The thinking architecture that determines what problems you can bring to AI at all.
- AI-Augmented Cognition — The fourth level of cognitive processing: AI as cognitive architecture extension.
Stage 8
- Integration Mastery — The governing meta-skill: when human judgment leads, and when AI carries.
WHERE TO START
If you are new to AI integration: Begin at Stage 1. Psychological Foundations and Dispositional Health is the competency most consistently skipped and most consistently responsible for good AI practices collapsing under pressure.
If you are already an active AI user: Your entry point is likely Stage 4 or Stage 7. Metacognitive Awareness surfaces the passive outsourcing that accumulates invisibly. Integration Mastery is the governing meta-skill most practitioners — regardless of experience — have never deliberately developed.
If you want the intellectual foundation first: Begin at Epistemic Cognition. Your domain expertise is your most valuable AI collaboration asset. This is where to understand why.
PATH TO ENGAGEMENT
The full framework is what every coaching engagement is built on. Which competencies your engagement primarily develops is determined at the Clarity Call.