Driving Security Team Adoption of Claude Opus
Habits, norms, and change management for adopting Claude Opus in a security team — turn a pilot into daily practice without burning analyst trust.
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
Habits, norms, and change management for adopting Claude Opus in a security team — turn a pilot into daily practice without burning analyst trust.
Habits, norms, and change management that make Claude stick in security and compliance teams — from champion to org-wide rollout.
A concrete cost model for Claude Opus in cybersecurity — where SOC time and money savings come from in triage, detection engineering, and analyst hours.
A concrete cost model for wiring Claude into your security and compliance stack via MCP — where time and money savings actually come from.
A safe, staged rollout for moving a security or compliance workflow onto a Claude agent — shadow mode, human-in-the-loop, and progressive cutover.
A staged playbook for moving a SOC workflow onto Claude Opus agents — shadow mode, human-in-the-loop, and progressive rollout without risk.
Build an eval loop that measures Claude Opus security-agent quality and gates releases with golden datasets, LLM-as-judge, and CI thresholds.
Build an eval loop that measures quality and gates releases for Claude agents connected to security and compliance tools.
Sandboxing, least privilege, secret handling, and prompt-injection defense for Claude Opus agents running inside real security infrastructure.