Product and Engineering Executive

Rolling out AI at enterprise scale.

I help large companies build AI into their products, their workforce, and the engineering factory that creates both. One insight from the field, every day.

Build the Data Platform Once

A field guide to building a governed customer data platform from collection through activation, with an architecture ready for AI agents.

02 / Operating model

Where AI creates leverage in a large company

01

AI for
customers

Useful, trustworthy AI capabilities embedded in customer-facing products: retrieval, personalization, conversational interfaces, and the evals that keep them honest.

02

AI for
employees

Governed access to models, tools, knowledge, and workflows: model gateways, usage and cost visibility, and adoption without shadow AI.

03 / Recent notes

The dispatch index

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  1. 01 Agent Skills: packaging what your org knows An Apache licensed spec for portable agent capabilities. The enterprise angle is that know-how stops being locked to one vendor's agent.
  2. 02 Open weights walk in the front door of GitHub Copilot Kimi K2.7 Code is the first open weight model in Copilot's picker. The story is distribution, not benchmarks.
  3. 03 Kimi K3 changes your leverage, not your stack The first open 3T-class model is here. Almost no enterprise will ever host it, and that is not where the value is.
  4. 04 MiniMax M3: judge it by the 24 hour run MiniMax's new flagship pairs a 1M token context with the metric that matters for agentic delivery: how long it stays coherent without a human.
  5. 05 Agents Need Eyes: The Verification Layer Is Arriving Chrome ships DevTools as an MCP server for coding agents. It is one of the clearest signals that verification, not code generation, is where agentic delivery gets decided.

04 / Work together

Bring your AI roadmap.
Leave with a clearer path.

Platform challenge, agentic delivery architecture, or an executive AI strategy session: let's talk about what actually moves the needle at scale.

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