Agentic AI Governance: Guardrails Before You Scale
Governance, trust, and safety for Claude agents — least-privilege tools, human approval on irreversible actions, audit logs, and evals leadership needs before scaling.
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
Governance, trust, and safety for Claude agents — least-privilege tools, human approval on irreversible actions, audit logs, and evals leadership needs before scaling.
Governance, trust, and safety for Claude agents: least-privilege scopes, audit trails, eval gates, and a staged-trust model leaders need before scaling.
How engineering teams actually adopt Claude agents — the habits, norms, and change management that turn a stalled pilot into a default way of building products.
Team adoption of Claude Code: the habits, norms, and change management that turn a pilot into a lasting practice instead of expensive shelfware.
Where the real time and money savings come from when building products with Claude agents — and the token, review, and rework costs that quietly erode ROI.
A grounded cost model for Claude Code: where the time and money savings actually come from, the costs teams forget, and how to measure ROI honestly.
A staged playbook for moving an existing workflow onto Claude agents: shadow mode, incremental tools, eval gates, and gradual rollout with instant rollback.
A staged playbook for moving an existing workflow onto a Claude agent: shadow mode, human-in-the-loop, incremental autonomy, and reliable rollback.
Build a Claude agent eval loop: gradeable rubrics, trajectory scoring, LLM-as-judge, and CI release gates that catch regressions before users do.