The Two Pillars of Data-Driven Product Organizations and Why AI Makes Them Non-Negotiable
What 15 years in the data ecosystem taught me about aligning product and data teams, treating data as a product, and preparing for what comes next
Modern Data 101
Conversations around Modern Data challenges, solutions, and innovations.
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How to Control AI Agents With the Data Platform You Already Have
Impact of the system surrounding models and how agentic performance and success changes based on system optimisation
The Human Side of AI: Cultivating Stewardship and a Culture of Trust
The Practical Roadmap for Building AI-Ready Data Foundations
What Human Memory Teaches Us About Building AI Memory
From Ebbinghaus’s forgetting curve to Murdock’s “lost middle,” the architecture of human memory offers a blueprint for autonomous AI.
Knowledge Graph for AI: Mapping Capabilities with Distilled AI Primitives
Leveraging the power of graphs to play with probabilities
The Layering Obsession in Data Architecture
The myth of architectural progress through more layers and the maximalist cult of "one more"
The Token Paradox: Why Cheaper Compute Produces Bigger Bills
Optimising the second variable with foundational architectural shifts
The Three Laws of AI Governance: The Case for Holding AI Agents Accountable Like Humans
Longest-running, most battle-tested distributed governance systems humanity has for coordinating agents
The Context Gap: Why Data Products Anchor AI Success
Urgency of bounded context and the architectural quantum of data that enables it.
The DBOM for Agent-to-Agent Trust Infrastructure
Uncovering the potential of Data Bill of Materials with broader readability, end-to-end traceability of trust, and simpler object management
Connecting Is Not Aligning: The Governance Gap Your Observability Stack Cannot Close
Why agentic AI fails on meaning instead of plumbing and what your organisation must own to close the gap.