From Agent Demos to Auditable Outcome Systems

Advanced evals: How to Find and Fix Hidden AI Failures in Your Product turns vague AI quality judgments into repeatable tests that expose failures in production-like conditions. This is Principle 16: Audit the Outcomes in practice: outcome engineers need evals that guide iteration, not just launch-day confidence.

Securing Tomorrow’s Git Forge for Agentic Software Development frames agent-generated code as an auditable system of session logs, injected context, and business ownership. That gives teams the provenance needed to review what an agent did, why it did it, and who is accountable—Principles 02 and 10.

VS Code 1.138 Brings Agent Sessions to Dev Containers puts agent sessions inside Dev Containers, adds Codex interoperability, and automates cleanup and reusable workflows. Isolated, repeatable execution environments turn coding agents into composable delivery infrastructure—Principles 07 and 09.

Okta Adds AI Agent Runtime Gateway and Forms Blueprint Alliance with AWS and CrowdStrike adds runtime enforcement and a broader kill switch for AI agents through identity and access controls. As agents gain permissions and operate across systems, explicit identity, policy boundaries, and emergency intervention become core platform capabilities—Principles 10 and 15.

Markdown in /src treats Markdown specifications as persisted source of truth from which agents can derive code and tests. Keeping intent, implementation, and verification close together makes agentic work more legible and reproducible—Principles 02, 06, and 13.