Risk management for Claude Cowork plugins at scale
Map blast radius, scope connectors, gate irreversible actions, and contain failures when deploying Claude Cowork plugins across the enterprise.
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
Map blast radius, scope connectors, gate irreversible actions, and contain failures when deploying Claude Cowork plugins across the enterprise.
The concrete skills and hiring shifts that make Claude Cowork plugins work across the enterprise — delegation literacy, plugin authors, and evaluation owners.
Scale Claude Cowork plugins from a pilot team to the whole enterprise without chaos: federated ownership, a governed catalog, shared connectors, and pruning.
Honest trade-offs on Claude Cowork plugins: where they clearly win, where a script or human is better, and how to choose without overspending on agents.
Permissions, approval gates, audit trails, and data boundaries leadership needs before scaling Claude Cowork plugins safely across an enterprise.
Habits, norms, and change management that make Claude Cowork plugins stick across enterprise teams — champions, triggers, and feedback loops beyond the launch email.
A concrete cost model for Claude Cowork plugins: where real time and money savings come from, how tokens drive variable cost, and how to measure ROI that survives an audit.
A staged plan to move an existing workflow onto Claude agents: shadow mode, human-in-the-loop, canary rollout, and safe rollback.
Build an eval loop for Claude agents: define metrics, score trajectories, use LLM judges, and gate every release on quality.