Writing from the work itself.
Short essays on data product strategy, AI delivery, open standards, governance, and the operating models that make product work practical.
Browse articles.
Practical writing on AI products, data products, standards, governance, and delivery.
13 published articles.
An AI Center of Excellence should turn scattered AI activity into repeatable product delivery, not become another central lab.
Read articlePalantir Ontology and the Maysano Product Graph both help agents use enterprise context, but they structure that context at different layers.
Read article When AI Agents Start Looking Like Data ProductsAI agents need the same product discipline as data products when they become reusable, governed business capabilities.
Read article What Anthropic Dreaming Tells Us About the Future of Data Product PortfoliosAnthropic Dreaming points toward a durable data product portfolio that preserves organizational context independently of any AI model.
Read article Workflow as Product in Data ProductsData product value depends on the workflow that keeps business context, decisions, delivery, and outcomes connected.
Read article Why a Data Product Catalog Was Not Enough for MaysanoMaysano needs a data product graph because catalogs manage inventory while agents need operating context, relationships, review, and approved shared memory.
Read article From Data Product Portfolio to Shared Memory for AI AgentsMaysano turns the data product portfolio into shared memory that helps AI agents follow governed, replayable runs.
Read article What Do Loop, Context, and Graph Engineering Have to Do With Data Products?Context, loop, and graph engineering show why data products need governed meaning, explicit relationships, and controlled operating workflows for AI agents.
Read article Golden Data Product PortfolioA Golden Data Product Portfolio helps leaders turn many separate data and AI ideas into one stronger implementation case.
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