Team Adoption of Claude Agent Orchestration That Sticks
Habits, norms, and change management that make Claude agent orchestration stick on real engineering teams — beyond the demo into daily workflow.
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 that make Claude agent orchestration stick on real engineering teams — beyond the demo into daily workflow.
A grounded cost model for Claude agent orchestration: where savings come from, the multi-agent token premium, and a payback formula you can defend.
A grounded cost model for using Claude and LLMs to secure source code — where triage hours, shift-left rework, and avoided-incident savings really come from.
Where zero-trust controls for Claude agents save real money: fewer incidents, faster audits, less rework, and a cost model you can defend to leadership.
A staged playbook for moving an existing workflow onto a Claude agent: shadow mode, suggest mode, scoped autonomy, feature flags, and instant rollback.
Move an existing workflow onto Claude agent orchestration with shadow mode, sliced cutover, automatic fallbacks, and instant rollback.
Stage the rollout of a Claude security agent: shadow mode, advisory comments, then narrow gating — moving an existing review workflow over without losing trust.
Build a labeled benchmark, measure precision and recall, and gate releases with an eval loop so a Claude security agent improves without silent regressions.
Measure Claude agent quality and gate releases with an eval loop: score tool-use trajectories, use LLM judges, build regression suites, and set CI thresholds.