Tuesday, October 13, 2026 | 7 mins read10/13/2026 | 7 mins read
Enterprise AI needs more than access to data—it needs business context. The same term, such as “oil production,” can mean different things to operations, refining, sales, and finance. Without governed definitions, relationships, metrics, ownership, and permissions, AI agents risk producing confident but inconsistent answers. I call this inefficiency the “Context Tax”: duplicated logic, conflicting KPIs, repeated reconciliation, wasted compute, and declining user trust. Microsoft, Snowflake, and Databricks are addressing this challenge through evolving semantic and ontology capabilities, with Microsoft also connecting business data to organizational knowledge and collaboration context. Leaders should start with one business domain, identify conflicting definitions, establish ownership, and test agents against real-world questions. Enterprise AI is often limited not by a lack of data or model intelligence, but by a lack of business context. Governed semantics can reduce ambiguity, improve explainability, and enable more consistent, trustworthy decisions.
Sunday, October 11, 2026 | 8 mins read10/11/2026 | 8 mins read
The article explores how to navigate career uncertainty by focusing on what we can control, preparing for what we cannot, and protecting our mental clarity during difficult times. It introduces the idea of <<Magneto helmet>> as a personal metaphor for maintaining focus, listening thoughtfully, and making deliberate decisions without shutting others out. Rather than letting uncertainty, external pressure, or fear dictate our actions, we should prioritize meaningful outcomes, continue learning, build relationships, and seek support when needed. Asking for help is not a weakness but a courageous skill that fosters connection, growth, and well-being. The article also offers practical advice: be specific about the help you need, approach the right people, communicate respectfully, express gratitude, and define a personal manifesto to guide future decisions. Ultimately, while we cannot control every circumstance, we can choose how we respond and take the next meaningful step.
Tuesday, October 6, 2026 | 6 mins read10/06/2026 | 6 mins read
This edition explores how Data and AI professionals can move beyond technology-first conversations to create measurable business outcomes. Drawing on consultative selling, it connects curiosity with Challenger, Value Selling, and MEDDPICC to clarify why change matters, quantify value, and navigate decisions. It also introduces Nemawashi as a thoughtful approach to stakeholder engagement and consensus-building. The central message is simple: technical expertise delivers greater value when combined with curiosity, measurable outcomes, stakeholder alignment, and the humility to revise assumptions.
Thursday, October 1, 2026 | 17 mins read10/01/2026 | 17 mins read
After several days at FabCon Barcelona, Pablo Junco sees Data Agents 2.0 as a major evolution—from simply talking to data toward understanding the business behind it. The key shift is context engineering: combining instructions, descriptions, examples, Topics, semantic models, Ontology, Graphs, and unstructured content so agents can retrieve the right business context before generating queries. Advanced NL2SQL/NL2DAX, smarter routing, observability, and richer sources move Data Agents closer to context-aware virtual analysts. Fabric IQ adds business meaning, while Work IQ could bring organizational context—what Pablo calls “Your Company IQ.” The goal is not just better answers, but trustworthy, governed, explainable intelligence that helps people and AI make sense of enterprise data. And this journey extends beyond analytics: Fabric Apps can turn governed data into production applications and workflows.
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