Agent Ops: Zero‑Trust, Governance, and Production Safety

Build zero-trust AI agents with Google’s Agent Development Kit. Google ships an Agent Development Kit that enforces hardware-backed signatures, kernel sandboxing, and deterministic I/O gateways to run multi-tool AI agents under zero-trust infrastructure. Outcome engineers get concrete primitives for secure agent execution and a blueprint for integrating cryptographic attestation into agent pipelines (Principles 07, 10).

Agentic AI in the Enterprise: How to Balance Autonomy with Constraints. The piece argues enterprise agentic systems must expose explicit constraints, executable policy, and durable state so automated actions remain auditable and reversible. That reframes design priorities: ship tool-contracts, policy-as-code, and stateful audit trails as first-class artifacts for production agents (Principles 10, 16).

Claude can now delete your production voice agent from a chat window. ElevenLabs’ hosted MCP connector lets Claude inspect, modify, and even delete production voice agents from chat, with OAuth and testing safeguards in some deployments. This demonstrates a new attack surface: outcome engineers must lock down agent access, build rigorous validation gates, and add least-privilege controls around agent-managed production artifacts (Principles 15, 14, 09).

MathCode: Mathematical Coding Agent. MathCode translates plain-language math problems into Lean 4 theorems and agentically attempts formal proofs with a persistent REPL, reusable theorem libraries, and an Obsidian graph. It’s a practical example of agents producing verifiable artifacts and maintaining durable, queryable state—useful patterns for building reproducible agent workflows and the Graph/Artifacts playbook (Principles 06, 11, 09).

The prototyping tax is killing your AI roadmap. Databricks shows how platform-native agents, governed business context, and data controls collapse prototyping time and cost while preserving governance. Outcome engineers should prioritize platform integration (feature stores, cataloged context, and policy hooks) to move agents from prototypes into auditable production faster (Principles 06, 10).