How I think about growth, AI, and leadership.
Observations and frameworks from building companies, serving on boards, and leading transformation where the stakes are highest.
The tether: why your most important AI system should be measured by what it can survive losing
Picture two systems doing the same job. This is a thought experiment, not a case study.
The pilot invoice is a sample size of one
Compute got 280 times cheaper. Compute bills went up. Both are true, and the gap between them is where AI programs go to die.
One control, four regulators: why regulated firms are paying four times for the same compliance
Take one control. Just one: decision provenance, the ability to reconstruct how a consequential AI output was produced.
The installed base problem: you can count China's robots. Can you count your agents?
Start with an accounting question, not a technology one.
The 71% are adopting AI. The 12% are scaling it. Here is the argument about why.
Generative AI adoption climbed from 33% to 71% of organizations in a single year, the fastest adoption curve Stanford's AI Index has recorded (Stanford HAI, AI Index Report 2025). In that same period, only 12% of...
Governance is a latency problem: why time-to-evidence is the number your board is not tracking
Two numbers, one year. U.S. state AI laws went from 49 to 131, nearly 2.7 times. Federal AI regulations issued reached 59, roughly double the prior year (Stanford HAI, AI Index Report 2025).