Thinking Out Loud
Topical strategy and AI perspectives written with the same rigor applied in client engagements. Specific enough to be useful, direct enough to share with your team.
The simplest way to make sense of Sam Altman: he is a large language model from ~2034, fine-tuned on the complete works of Y Combinator, and instructed to build the very thing he keeps warning us about. The evidence is in the outputs.
The MIT finding on AI pilot failure is not a verdict on the technology. It is a verdict on procurement. The 5 percent that worked share a structural posture toward scope and accountability; it is teachable.
The Gates Foundation's malaria intervention points to a deeper lesson: philanthropic capital creates far greater impact when deployed with analytical discipline: the same rigor that governs effective investment capital.
A curious pattern is appearing across organizations. People use AI constantly, then remove all visible traces of it. This is not a technology story. It is a professional norm story.
You can have a sharp strategy and still fail to execute it. In most organizations, the gap is not vision. It is measurement.
An operating model is not a diagram. It is how work flows from idea to production and who is accountable at each step. Here is what actually matters.
Valuation rewards outcomes, not activity. Here is what the data actually says about value creation and where companies routinely overspend with little return.
C-suite transitions are deceptively fragile. Up to 40% of senior executives fail within 18 months. The difference is sequencing.