The work, published in the open.
The Issues take a single argument apart and build it to use. The FAQs are short, sendable answers to what I get asked most. The Case Studies dissect the system at work in the real world. Every piece names something, explains something, or hands you something you can use on Monday.
The Issues
The standing edition. Each one takes a single argument apart and builds it to use.
The FAQs
Short, sendable answers to the questions I get asked most.
The Case Studies
The system at work in the real world, dissected honestly.
The Issues
All 29 →-
The Contours of an AI Team
There are two jobs hiding inside the decision to build an AI team, and they call for different investments. One IT can handle. The other, changing how the company works, needs a small team of four built in a shape that barely existed five years ago.
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Write the Role Before You Fill It
You cannot hire, grow, or even fractionally assign a job you have never written down. Defining the AI Product Partner is the first real act of the transformation, not the paperwork after it.
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Inside the Role
We had engineers. We had data scientists. The hard part was not what we could build. It was whether people would trust it enough to use it.
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The Demo Is a Question, Not an Answer
Ninety-five percent of AI pilots are said to fail. They fail because companies invest before they prove adoption. Reverse the order, and let the demo find the truth instead of selling a future.
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People First, or Not at All
A company can deploy every AI tool and change nothing. Deployment is not adoption, and the gap between them is people. You close it people-first, or the transformation does not hold.
The FAQs
All 29 →-
When do I add the next person, and to which seat?
Weight the hires to the top of the funnel. The deep engineering seats compound; the enablement seats hit their ceiling first.
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What does an AI Product Partner actually do all week?
Less than the title suggests and more than a calendar shows. The clearest picture of the job is one real week, from the morning briefing they built to the two lines they write in the board deck.
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How does the AI Product Partner role actually start?
Not on an org chart. Point a trusted translator at a real, cross-functional problem, and let the role reveal itself before you name it.
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How do I keep an AI pilot from stalling?
Stop letting a demo authorize a build. Prove adoption at each rung before you fund the next, and let the prototype find the real problem instead of selling a roadmap.
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We have the tools. No one's using them. Now what?
The problem is not the tools; it is that deploying a tool is not the same as adopting it. Adoption is a people problem, and you fix it people-first, not by buying more software.
The Case Studies
All 7 →Read against the Scope Ladder: five sizes of change, from a habit you build in an afternoon to a company you re-align over a year, and what each one actually produced, across outcomes from efficiency to translational capacity.
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Four Rungs, and the Courage to Stop
How Avidity ran AI pilots so few of them ever stalled. An AIPP at intake, a Sub24-to-Platform ladder gated by traction, and the discipline to stop an ask the moment the pain was already solved.
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The Shaping Cone
How a function defaulted to the department of no became the engine of responsible speed. IT reframed as Innovation Technology, reporting high, with governance as the shaping cone rather than the brake.
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Fifteen Minutes at a Time
At Avidity the AI policy was written by Legal, IT, and my team. Then I personally trained more than half the company on it, fifteen minutes at a time, because a policy that cannot be understood is functionally not a policy.
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The 72-Hour Transcript
Everyone wanted AI meeting transcripts, and everyone feared them, the wrong details and the permanent discoverable record. The fix was to make the transcript delete itself in 72 hours, and to make downloading it the act that assigned responsibility, under company policy, for finalizing the record.
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Better Than a Blank Page
A wall of INDs and BLAs the writing team could not reach, and twelve months of no. Then three days in a room proved that a first draft at 60 to 75 percent beats a blank page, and a resistant team finally had its aha.
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