Intellectual library
Insights & frameworks
Articles, frameworks and reports organised around the five institutional questions that matter.
Learning in the AI era: the series map
12 reflections on learning, human judgment and systemic transformation in the AI era. The complete index of the series.
July 27, 2026
The final product is dead as evidence of learning
When any essay can be generated with AI, assessment must migrate from product to process: reasoning, decisions, iterations and defence of knowledge.
July 20, 2026
The education that gains value in the AI era
The more capabilities AI amplifies, the more value an education gains when it can develop judgment, autonomy, purpose and the capacity to transform reality. The synthesis of the series.
July 20, 2026
The graduate profile as a living system
The graduate profile comes alive when it guides what is designed, what is accompanied, what is assessed and what an institution is able to evidence. Five connected dimensions.
July 13, 2026
University Learning Architecture: a framework for the AI era
Purpose → educational model → graduate profile → curriculum → experiences → assessment → evidence → impact. A macro–meso–micro framework to transform universities.
July 10, 2026
Process as evidence in the AI era
When producing becomes more accessible, the real educational value lies in making visible how learning is built: how people think, decide, collaborate, improve and transfer.
July 6, 2026
Macro, meso and micro: three layers to transform learning
One experience can inspire. Three connected layers can transform. Purpose, curriculum, assessment, culture, technology, experiences and evidence connected.
June 29, 2026
What capabilities must a person develop when AI can answer?
The human graduate profile in the AI era: technological and human capabilities, competency progression and evidence connected to employability.
June 28, 2026
Scaling experiential learning with purpose, sustainability and foundations
Moving from isolated experiences to systems that sustain deep learning. The great opportunity is not doing more experiences: it is getting more people to live experiences that truly transform.
June 22, 2026
Substitutive AI or expansive AI
The difference lies in whether the experience reduces or expands understanding, judgment and transferable learning. The same tool can produce opposite educational effects.
June 15, 2026
AI agents: when execution is automated, judgment becomes central
As AI makes execution easier, educational value shifts towards intention, judgment, orchestration, feedback and evidence of learning.
June 8, 2026
When generative AI changed the scale
What used to require hours or days of work can now be generated in seconds. That new scale transforms what we observe, assess and value. The illusion of understanding is the great educational challenge.
June 1, 2026
AI in education did not start with ChatGPT
More than a decade of adaptive systems, learning analytics, recommendation, automated assessment and intelligent tutors. What changes with generative AI is the scale, the accessibility and the visibility of the debate.
May 25, 2026
Covering content is not the same as generating learning
An institution can cover an entire syllabus and still not have created the conditions for learning to happen with depth. What learning needs in order to occur.
May 18, 2026
The first crack: teaching was always much more than covering a syllabus
The origin of an educational unease: accompanying development, not administering content. Before, teaching meant covering. Today, teaching means helping people grow.
May 11, 2026
What does learning mean when producing answers is no longer the hard part?
AI does not eliminate the need to learn: it makes visible that producing with help does not equal learning with depth. Six principles on how students learn.
May 4, 2026