Insights
Practical perspectives on driving impact at scale with AI: what works, what fails, and why people and process decide most of the outcome.
AI Transformation
May 2026 · 6 min read
The Intelligent Organization
Durable value in enterprise AI comes from encoding institutional knowledge, incorporating feedback, and building learning loops that compound into a knowledge moat.
Read article →June 2026 · 7 min read
The AI Playbook
The recurring building blocks of a production AI system, from prompt engineering and RAG to orchestration and evals, in the order you adopt them.
Read article →June 2026 · 5 min read
Bridging the Demo-to-Production Gap
A vibe-coded prototype is not a production system. The four kinds of engineering that close the gap: system integrations, prompting and context engineering, QA and eval sets, and security and governance.
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