Professional judgment remains with the architect.
Machine assistance changes the production process, not the professional responsibility attached to the work.
First Public Edition · Version 1.0 · September 4, 2026
Verification and Documentation of Machine-Assisted Work in Architectural Practice
An author-developed voluntary practice framework for licensed architects and architectural firms.
The premise
Artificial intelligence has not altered the architect's standard of care. It has created new ways to breach it, at a speed that has outrun the profession's capacity to verify what it seals.
What the Guide contributes
The sources state the obligation. The Guide supplies the working method.
Verification is defined as an operation.
A stated criterion, an authoritative source, and a recorded result replace general review with a test that can pass or fail.
The work can be reconstructed.
The record identifies what was machine-assisted, how it was verified, by whom, when, and with what disposition.
The complete publication
Read by Part
Part IPart IIPart IIIPart IVPart VPart VIA–G
The Condition Observed
The production-verification gap and the questions it creates.
The Seven Principles
Responsible control, verification, provenance, competence, confidentiality, records, and boundaries.
Reasonable Control by Failure Surface
Architecture-specific controls for the places machine assistance can fail.
The Record
The project context and verification entries that make the work reconstructable.
When the Record Is Examined
What adoption and conformance can show when the firm must account for its work.
Implementation and Conformance
Installation at three practice scales and the Guide’s conformance statement.
Appendices
The model policy, classification, protocols, record specification, checklist, conformance language, and glossary.
From publication to practice
The Guide is complete by design. Implementation remains firm-specific.
Assessment, professional education, and implementation consulting help firms fit the method to their services, staffing, jurisdictions, and existing quality-control systems.