Version 4.5
The AI Literacy Ladder
A learning framework for non-technical people to become familiar and productive with generative AI. It's the result of three years' study — over 2,000 hours — and live work with groups across Europe in healthcare, creative industries, education, public services and service design. It keeps adapting as the tools and people's needs change.
- 1
General theory
How generative AI systems are made and how they function — what they can do, what they can't, and why. The grounding everything else builds on.
- 2
Context engineering
Getting useful, reliable results from AI tools — prompt engineering and managing the information you give a model to reduce errors.
- 3
Model & interface selection
Choosing the right model and interface for the job — and knowing where your data is processed — to fit your context and goal.
- 4
Retrieval-augmented generation
Using your own data with AI, and choosing the right retrieval method for your specific use case.
- 5
Tool use
Connecting AI to external tools — email, calendar, booking systems — to expand what it can actually do.
- 6
Agents
AI systems that reason, use tools and pursue a goal autonomously — simpler to build than it sounds, and a real productivity lever.
- 7
Multi-agent frameworks
Coordinating several agents through an orchestration layer to carry out complex tasks — and knowing when it's worth the added fragility.
- 8
Fine-tuning
Refining a model on your own data, or making it smaller — for more accuracy, fewer hallucinations, and lower running cost.
Developed by Esko Reinikainen. Start climbing →