Three problems, one way of solving them.
Each of these is a different kind of organization with a different kind of failure. The work underneath them is the same: find the layer where the real problem lives, build the infrastructure that operates at that layer, and make decisions cheaper to reach.
- AMC Networks
- Complex execution at scale
- Kaseya
- Executive decision infrastructure
- KLJ Ventures
- AI-native operating systems
One client. Five years. The operating model behind 16 business units.
A fast-growing streaming portfolio running on processes built for something smaller. Teams spent their time reconciling information rather than moving campaigns forward. The fix was not a better tool, it was an operating system new work could plug into, including the partner rollouts that would otherwise have each arrived with their own process.
Read the case study →14 companies, one operating model.
A private-equity roll-up acquiring faster than it could absorb, where every acquisition arrived with its own systems, metrics and definitions. Leadership could not compare anything to anything, which is a capital allocation problem disguised as a reporting problem. Includes the acquisition they decided not to make.
Read the case study →I caught my own AI system fabricating, and rebuilt it.
The first version produced a lot of output. Some of it was excellent and some was confidently, fluently wrong. What changed everything was deciding to treat fabrication as a bug with a cause and a fix, rather than an inherent property to be tolerated. That reframing is what turned a collection of prompts into an operating system.
Read the case study →If you have a mandate that needs an owner, let’s talk.
A 20-minute call is the fastest way to find out whether I am useful.