Automated quality and human control
Development checks, security improvements, and an evidence plan for supervised AI.
Quality that does not rely on memory
At this stage, the product development process added eleven automated checks. Types, accessibility, localization, visual consistency, and tests are part of validation work. These are development controls, not eleven user-facing approval gates or a guarantee that defects cannot occur.
Built for supervised AI
We defined the implementation path for activity logs, content provenance, and consent. Teams should be able to reconstruct what an agent did, which information it used, and under whose authority it acted.
Availability reviewed September 8, 2026: activity and records remain in Preview, and gates are a Pilot. This plan does not establish legal compliance or confirm that all its components are available. The current AI Act guide separates scope, evidence, and applicable dates.
Security in the details
We reviewed file-upload surfaces, hardened filename validation, and reduced operational noise in production. Permission, approval, and workspace-isolation tests also gained broader coverage.
These improvements share one idea: autonomy is only useful when its boundaries are visible and verifiable.