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 Biotech of Tomorrow
You cannot build the biotech of tomorrow by making the biotech of yesterday slightly more efficient. The founding argument of Translational Intelligence.
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There Is No AI Work Product
The first thing every leader asks is what their AI policy should be. The whole answer fits in one sentence, and it moves accountability to exactly one place.
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An Afternoon, or a Restructure
The word transformation hides five different sizes of change, from a habit you can build before lunch to a company you have to take apart and rebuild. Naming the size is most of the work.
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A Policy Is Only as Good as It Is Understood
Writing an AI policy is the part everyone expects to be hard. It is not. The hard part is teaching it, in person, until a company understands it well enough to act, and can eventually teach it to itself.
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Don't Point AI at Your Best Work
The instinct is to aim AI at your hardest, most important work. Often backwards. Point it at the work that is high value to the business and low value as a use of your best people, and spend the bandwidth you free on the work only they can do.
The FAQs
All 29 →-
Isn't efficiency a good place to start?
Yes, as the on-ramp. No, as the destination. Take the hours back, then spend them on redesign, not on a faster version of the same company.
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What if legal wants a longer, stricter AI policy?
A longer policy no one reads protects no one. The one-page version is not lax; it is the enforceable one.
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Which rung of the ladder should I start on?
Almost always one rung lower than your instinct. Start where you can make something real this quarter, then compose upward.
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Isn't teaching the whole company the policy too expensive?
Yes, and the expense is the point. Senior time spent teaching is the signal that the policy matters. The cheap alternative, a PDF on a shared drive, is what produces a policy nobody follows.
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Should I keep AI away from my most important work?
Not never. But in a resource-constrained shop, point it at the low-judgment work first, and spend the bandwidth you free on the work only your best people can do.
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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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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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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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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