RLK Unfiltered
Not a list of things you could Google on your own. Perspectives written with the same rigor applied in client engagements, specific enough to be useful, direct enough to share with your team.
The agent wins on sticker price. But the salary was never buying year-one output. It was buying your 2031 senior team, and the apprenticeship deal that produced it just collapsed. Here is the math, and the opening it creates.
Machine identities outnumber your humans 82 to 1, and AI agents are turning those credentials into coworkers with no manager and no offboarding. An airline already tried blaming one in court. It went badly.
Companies that buy AI from vendors succeed far more often than the ones that build it in-house. Yet mid-market teams keep spending engineering on capabilities a vendor already sells, then buy their one real differentiator off the shelf. Here is how to tell the difference.
AI buying decisions are being made by the people who understand the technology. They should be made by the people who understand the money. Your CFO is the most undertapped AI leader in your company, and the reason is structural.
The pilot worked. The demo was impressive. Leadership is excited. And in six months, nothing will have changed. The gap between a successful AI pilot and captured economic value is where most companies lose, and almost nobody is talking about why.
The companies that say they can't figure out AI can usually figure out AI just fine. What they can't figure out is who is allowed to say yes. Authority structure, not tool selection, is the binding constraint on AI value capture in the mid-market.
The phrase is doing damage. When a program is called AI strategy, the team optimizes the AI. The strategy lives at the workflow. The AI is the instrument. Programs that move numbers are organized around the workflow. Programs that produce activity reports are organized around the technology.
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 isn't vision. It's 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.