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Insights / Field Notes

Field notes on data & AI

Practical perspectives on turning data infrastructure into measurable enterprise value — methodology over hype.

fractional-cdo

Sep 4, 2026·5 min read

A Fractional CDO Is Not a Vendor With a Better Title

A fractional CDO is part-time data leadership. If the engagement needs a tool sale, a catalog-first roadmap, or their constant presence, you hired a vendor.

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Your Model Did Not Get Worse. The Data Moved.

data-drift

Aug 28, 2026·8 min read

Your Model Did Not Get Worse. The Data Moved.

Data drift is a change in the data your model sees after you train it. Here is how you recognize it, and how you solve it, without guessing.

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Traditional Analytics Is the Starting Point for AI Platforms

AI and Data

Aug 14, 2026·5 min read

Traditional Analytics Is the Starting Point for AI Platforms

Experienced data people are being told they need to become something else to stay relevant. They do not. The work they already know how to do is the work that makes an AI platform real.

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Consultants

Aug 13, 2026·5 min read

The Best Consultants Work Themselves Out of a Job

Every incentive in consulting pushes toward keeping the client dependent on you — dependency protects the invoice. I think that's the wrong strategy, both ethically and commercially. The best fractional and advisory engagements build a path to self-sufficiency: documenting the reasoning behind decisions, involving internal teams in the build instead of just the handoff, and teaching when time allows rather than just delivering. Clients who become capable because of you refer you to the next three companies. Clients who stay dependent eventually resent it. Mentorship isn't in tension with a sustainable practice — it's what makes one.

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Before You Buy an AI Roadmap, Buy a Data Quality One

data observability

Jul 31, 2026·5 min read

Before You Buy an AI Roadmap, Buy a Data Quality One

Gartner predicts 60% of AI projects lacking AI-ready data will be abandoned through 2026 — and only 12% of organizations say their data is actually good enough to support AI. Most companies chasing AI right now are building on data they don't trust, and reaching for a data catalog first because it's the easiest thing to demo. But a catalog just makes untrustworthy data easier to find. This piece makes the case for a different order: observability and quality on your critical data paths first, catalog second, AI initiative third — not the reverse.

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Jul 31, 2026·5 min read

Agentic AI for the Rest of Us: What's Actually Worth Doing (and What Will Quietly Wreck Your Budget)

Don't skip agentic AI. But, it means be specific about where you use it — and this week I wrote about the 3 places it actually pays off for a small business (not an enterprise), plus the 5 things that keep the bill predictable.

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Jul 21, 2026·5 min read

Making Waves: Why Data Leaders Need Dissent to Drive AI-Era Decisions

Early in my career, I was labeled a troublemaker. I disagreed too often, pushed back too hard, and once someone decides you're "difficult," that label sticks no matter what you do next. It took years of studying how the best technical leaders operate for me to realize the problem was never that I disagreed — it was that I argued without evidence. In a data organization, that's the one unforgivable sin.

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AI Readiness

Jul 15, 2026·6 min read

AI Readiness Starts With Data, Not Models

Why most enterprise AI stalls at the pilot stage — and the data foundations that separate the ones that scale from the ones that stall.

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Data Governance

Jul 8, 2026·5 min read

Data Governance Is an Operating System, Not a Policy

Data governance has a branding problem. Stripped of the paperwork, it's the operating system that lets you scale decisions without losing trust.

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