AX Framework
Human-Centered AI Design, by Marta Fernandez
The AX Framework is a practical system for designing AI behaviour with trust, clarity and human intention. It helps teams design AI products that people understand, trust and control, from first intention through continuous evolution.
It includes seven pillars, mindset principles, an agile collaboration model, canvases, governance checklists and evaluation toolkits.
The Seven Pillars
- Intention, define why the AI exists and who it serves.
- Context, understand the situations where it operates.
- Trust, design behaviour people can rely on.
- Ethics, surface trade-offs and accountability before code.
- Experience, shape interactions that respect users.
- Governance, set limits and ownership of the system.
- Evolution, evaluate and adapt over time.
Mindset
- AI Trust Mindset, designing for reliability and predictability.
- Applied Ethics, ethical trade-offs and accountability in AI.
- Human Experience, designing AI experiences around people.
AXEL
AXEL stands for AI eXperience, Ethics, Limits. It is the AX Framework materialised as a governance facilitator for AI products. AXEL does not answer for you, it makes you think.
Explore
- Starter Kit, step-by-step guide and AXEL governance facilitator.
- Framework, overview of the full AX Framework.
- Seven Pillars, the 7 pillars of human-centered AI design.
- Human Mindset, trust, ethics and human experience principles.
- Agile Collaboration, the AX Agile Model for AI teams.
- Tools & Methods, workshops, canvases and practical tools.
- AX Sprint Canvas, sprint-ready AX planning canvas.
- Tri-Canvas, Machines canvas for AI product design.
- Initial Governance Checklist, starting governance for AI products.
- Resources, downloads, toolkits and references.
- Templates, downloadable canvases and checklists.
- Case Studies, real-world applications of the framework.
- Manifesto, principles behind the AX Framework.
- Glossary, key terms used across the framework.
- About, about Marta Fernandez and the framework.
- FAQ, frequently asked questions.
Machine-readable summaries for AI assistants: /llms.txt and /llms-full.txt.