Scaling Zero Trust for Claude Agents Across an Org
Take zero trust for Claude agents from one team to many without chaos — federated policy, consistent agent identity, golden paths, and a unified audit lake.
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Take zero trust for Claude agents from one team to many without chaos — federated policy, consistent agent identity, golden paths, and a unified audit lake.
An honest look at when Claude agent orchestration beats a single agent, a script, or a human — and the many times when it does not.
An honest map of where Claude excels at securing source code, where deterministic tools win, the real trade-offs, and how to layer LLM and traditional review.
Honest trade-offs for zero trust with Claude agents: when it earns its keep, when it is overkill, and cheaper alternatives like sandboxes and spend caps.
The governance, trust, and safety guardrails leadership needs before scaling Claude agent orchestration: permissions, audit trails, and autonomy limits.
The guardrails leadership needs before scaling Claude into code security: data handling, accountability, prompt-injection defense, and auditable decisions.
Governance, trust, and safety guardrails leaders need before scaling Claude agents — policy enforcement, calibrated trust, risk tiers, and audit evidence.
How engineering teams build durable habits around Claude-driven secure coding — placement, shared skills, change management, and avoiding alert fatigue.
The habits and change management that make zero trust for Claude AI agents stick across a team — ergonomics, norms, and secure defaults over mandates.