Agents Need Faster Feedback—and Harder Boundaries

Linear reworks CI for AI-speed development. With a quadrupled test suite, Linear cuts validation latency and runner costs so generated code does not queue behind the pipeline—Principle 16: Audit the Outcomes.

GitHub issues become an agent coordination protocol. Bram uses issues as an auditable handoff layer across models, machines, and sessions, giving multi-agent work durable state and traceability—Principle 09: Agentic Coordination is a New Org.

EvalEval makes benchmark results reproducible. UK AISI’s evaluation cards capture schemas, configurations, and evidence behind benchmark claims, giving practitioners a way to compare systems without trusting opaque leaderboards—Principle 02: Ground Truth and Principle 16: Audit the Outcomes.

Okta adds a runtime gateway for AI agents. Runtime enforcement, identity controls, and a broader kill switch move agent governance from policy documents into the execution path—Principle 15: The Gate.

Drop sandboxes coding agents with rootless isolation. The new sandbox combines configurable permissions with optional gVisor protection, giving builders a practical containment layer for agents that run code or handle untrusted programs—Principle 14: The Immune System.