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title How to cite
version 0.5.1
canonical https://www.ainativeoffice.org/cite/

Cite This Specification

Canonical citation formats for the AI-Native Office specification: BibTeX, APA, Chicago, IEEE, and CITATION.cff, with permanent clause-level and version-level identifiers.

BibTeX

@techreport{ainativeoffice2026, title = {{The AI-Native Office: The Room as the Machine}}, author = {Timothy Walsh and Parham Alizadeh}, institution = {The AI-Native Office}, type = {Draft Specification (RFC)}, number = {v0.5.1}, year = {2026}, url = {https://www.ainativeoffice.org/}, doi = {10.5281/zenodo.21650157}, note = {Revised 2026-07-22} }

APA 7th edition

Walsh, T., & Alizadeh, P. (2026). The AI-Native Office: The Room as the Machine (Version 0.5.1) [Draft specification]. The AI-Native Office. https://doi.org/10.5281/zenodo.21650157

Chicago 17th edition

Walsh, Timothy, and Parham Alizadeh. "The AI-Native Office: The Room as the Machine." Version 0.5.1. Draft specification. The AI-Native Office, 2026. https://doi.org/10.5281/zenodo.21650157

IEEE

T. Walsh and P. Alizadeh, "The AI-Native Office: The Room as the Machine," The AI-Native Office, Draft Specification v0.5.1, 2026. [Online]. Available: https://www.ainativeoffice.org/

CITATION.cff

cff-version: 1.2.0 message: "If you reference this specification, please cite it as below." title: "The AI-Native Office: The Room as the Machine" version: "0.5.1" date-released: "2026-07-22" url: "https://www.ainativeoffice.org/" repository-code: "https://github.com/ainativeoffice/ai-native-office-spec" doi: "10.5281/zenodo.21650157" type: software license: CC-BY-4.0 keywords:

  • AI-native office
  • agentic office
  • sovereign compute
  • on-premises inference
  • zero egress
  • data sovereignty
  • edge inference
  • ambient intelligence
  • commercial real estate
  • regulated industries
  • Model Context Protocol abstract: >- The institutions best positioned to leverage frontier AI — regulated banks, law firms, healthcare systems, and the firms that serve them — are precisely the institutions least able to use it as delivered. Data residency obligations, model governance requirements, and the fundamental exposure of routing sensitive inference through shared hyperscaler infrastructure have created a structural ceiling on enterprise AI adoption. The AI-Native Office removes that ceiling by defining a new commercial real estate asset class: a sovereign, on-premises compute node built within a Class-A office environment, acoustically hardened to STC 55 and powered by tenant-owned inference silicon. Ambient multimodal data is ingested and processed locally — never crossing a public network boundary — delivering absolute data sovereignty, zero egress cost, and deterministic AI inference at the point where collaboration actually happens. authors:
  • given-names: "Timothy" family-names: "Walsh" email: "tw@ainativeoffice.org" affiliation: "TruCast"
  • given-names: "Parham" family-names: "Alizadeh" email: "parham@ainativeoffice.org" affiliation: "North Castle Ventures" identifiers:
  • type: doi value: "10.5281/zenodo.21650157" description: "Concept DOI — always resolves to the latest version."