Thinking Tools
Frameworks and mental models distilled from decades of leading technology and people
Applied Framework: Diffusion of Innovation By Everett Rogers
Perhaps the real innovation isn’t in the technology itself. It is in our willingness to finally see it. As AI makes long-existing capabilities newly visible, leaders must separate what just became possible from what was simply waiting for permission, and ask: “Has this already existed, and are we only now ready to see it?”
Assurance Engineering™
As AI generates more of the software we rely on, a critical gap is opening between production and proof. The Assurance Engineering mental model suggests that trust in AI-generated artifacts requires more than better tools. Organizations need a dedicated function to validate that those artifacts are correct, safe, explainable, and maintainable.
No-Proof Nod™
A claim that technology eliminated a role, skill, or function is a verdict, not evidence, until it is tested. Before accepting it, separate the task that was automated from the contribution it carried, and ask: “Was the contribution located in the task itself, or in the judgment, interpretation, or imagination that surrounded it?
The Journey, Objective, Yield (JOY) Framework™
A destination tells you only whether you arrived. The journey tells you what you now know. The JOY Framework™ measures that journey with the same rigour as the destination because the Yield it produces is an asset in its own right.
It builds on SMART goals, OKRs, and PDCA, extending them by treating the journey itself as a measurable asset.
The No-Line Principle™
Work-life balance has become one of the defining struggles of modern work, yet the discomfort rarely comes from an uneven split of hours. The No-Line Principle argues it comes from treating work and life as opposing forces in the first place. Bees don’t balance the two, they simply live, which is the harder question this model asks leaders to sit with.
The Outsider’s Lens™
The people closest to a system are often the last to see it clearly. Familiarity replaces observation with assumption and assumption is where blind spots live. Find the person who hasn’t yet learned to look past the obvious. Their confusion is your most honest diagnostic.
The Zero-Impact Scenario (ZIS)™
Innovation should not be measured solely by what it adds, but by what would be lost if it never existed. As AI lowers the cost of creation, leaders must separate what’s possible from what’s necessary and ask: “If this disappeared tomorrow, what would actually happen?”