writing
Notes on AI, delivery, and adoption.
Answer-first essays on getting AI from pilot to production: architecture, enablement, and the agentic systems behind it.
Why AI pilots stall before production
AI pilots stall because they optimise for a demo, not for adoption. Production requires architecture, guardrails, and a change in how teams work, not a better model.
ai-adoption enablement
Designing MCP systems for real teams
Good MCP systems expose a few high-leverage tools with clear boundaries, not every API you have. Scope, access control, and observability matter more than autonomy.
mcp agents
What 700 trained engineers taught me about adoption
After training 700+ practitioners, the pattern is clear: adoption is a behaviour change, not a tooling rollout. Role-specific practice and internal champions are what make it stick.
enablement ai-adoption