Source
The two papers
Open preprints. CC BY 4.0. Both on Zenodo.
Everything on this site derives from two papers published on Zenodo in 2026. The Moonshot paper makes the political case; the Architecture paper describes the eight-layer technical model. Read either standalone, or both as a pair. They are licensed CC BY 4.0 — quote, translate, adapt, build on, criticise. Attribution is required; permission is not.
Matthias Pochmann · 2026
The European Moonshot for Education
AI-Powered Learning as Sovereign Infrastructure
What it argues
A proposal for the twelfth Moonshot project in the EU Multiannual Financial Framework 2028–2034. AI-powered education has been deployed at planetary scale by a single platform; the architecture decision has already been made — by no government. The paper argues that cognitive sovereignty is the next link in the European sovereignty chain (chip → data → digital → cognitive) and that the first step is a feasibility study, not a build order. Precedent: CERN, Galileo, GSM.
- Open on Zenodo
- zenodo.org/records/18759299
- License
- CC BY 4.0 — share and adapt with attribution
Cite as
Pochmann, M. (2026). The European Moonshot for Education: AI-Powered Learning as Sovereign Infrastructure. Zenodo. https://doi.org/10.5281/zenodo.18759299
Matthias Pochmann · 2026
A Generative Education Architecture for Planetary-Scale Personalized Learning
The eight-layer technical model
What it argues
The technical companion to the Moonshot paper. Decomposes AI-mediated learning into eight interoperating layers — from the Mentor (the only actor) through the Learner Profile (the pivot), the Didactic Model, Data Sovereignty, the Federated Knowledge Graph, the Competency Evidence System, Autonomous Hub Infrastructure and Trustee Governance. Nine design principles. A full dependency graph. The architecture treats sovereignty as a property of structure, not policy.
- Open on Zenodo
- zenodo.org/records/18759134
- License
- CC BY 4.0 — share and adapt with attribution
Cite as
Pochmann, M. (2026). A Generative Education Architecture for Planetary-Scale Personalized Learning. Zenodo. https://doi.org/10.5281/zenodo.18759134