Principle 05
Design for systems that get stronger over time.
The measure of a leader's work is what still functions, and improves, after they leave the room.
What I mean
Two solutions can produce the same result this quarter and diverge completely over three years. One depends on the people who built it; the other captures learning, so every use makes the next one better. Building the second kind is slower and is almost always the right call.
Why it matters
Heroics do not compound; they create dependency. Systems that capture their own feedback compound quietly. At director and VP level, compounding is the entire job. You are judged on the trajectory you leave behind, not the output you personally produced.
What it looks like in practice
- 01Build the feedback loop into the workflow, not into someone's calendar.
- 02Prefer shared infrastructure over point solutions, even when the point solution ships sooner.
- 03Write the patterns down: playbooks, golden paths, templates, so good practice is the default path.
- 04Develop people deliberately. The most durable system you build is the group of people who can rebuild it.
From my work
Centralized access, routing, and telemetry meant every new AI use case inherited cost controls and audit trails by default. The reusable patterns kept scaling after the original implementations were done.
Building AI Transformation from the Work UpContact
Let's get into it.
Ambiguous problem, AI adoption that stalled, an operating model that stopped scaling, a support function that should be a product. That is the conversation I want.