Perspectives & Writeups
This is not the author's blog — it is a record of the broader body of discussion developing around this research: original pieces the whitepaper draws on, independent third-party applications and interpretations, and critical challenges to its assumptions or conclusions. Inclusion here does not imply endorsement, and a piece is not excluded simply because it disagrees with the framework — a credible reference foundation should make disagreement inspectable, not hidden.
Open an issue or pull request on the GitHub repository with your piece's title, author, date, publication, URL, and a short description — see perspectives/README.md for the entry format. This catches LinkedIn posts, newsletters, PDFs, videos, and podcasts that automated discovery may not find reliably.
3 entries.
Who Owns Your AI
Frames AI infrastructure across three layers — Compute as Infrastructure, Intelligence as Utility, and Personal Superintelligence — and argues that true digital sovereignty requires ownership of infrastructure, information, and agents, plus portability of context between providers. Source of the 'information as AI's operating system' framing used in the whitepaper.
So, the majority agrees: the time for digital sovereignty has come, now what?
Proposes a cooperative-ownership model for shared AI compute, with a published cost-sharing calculation (~€42/member/month at 50 members, ~€21/member/month at 100). The whitepaper's Global Baseline and Token-Factory workbooks reconcile this figure against a separately-computed DGX-Spark-pool cost (~€19.50-23/member/month) as two different hardware tiers, not a discrepancy.
The Overlooked AI Scale-Up Layer
Argues owner-managed SMEs — firms with existing customers, revenue, and operational knowledge — are structurally well positioned to benefit from agentic AI because the opportunity is delivery innovation, not product innovation, paired with a 'globally local' expansion pattern. Source of the whitepaper's SME/owner-manager lens (Section 38).