Most organisations still run on ideas built for a world where machines couldn’t replace people. AI has ended that bargain. Theory X, utilisation targets, the tyranny of the plan: paradigms that once merely capped what a transformation could reach have turned lethal. What’s needed now isn’t more consulting, or more AI on top of the old paradigm, but coaching of a kind that refuses to shortcut, and a community to make the crossing with. No leader whose paradigm is dying makes that passage alone.
Come Prepared to Die
An Engineering Leader’s Field Guide to the Leadership Paradigms AI Is Exposing
Serialising now, two chapters a week here and on LinkedIn; the serialisation finishes in early September 2026. The death in the title is the old leadership paradigm and the identity built on it. Each axis chapter stands alone; if you’re new, start with chapter 1 below.
Want the whole argument first? Read the essay that became the book, the core ideas end to end, about a 30-minute read. Who I am and how I coach are on my About page.
Come Prepared to Die: An Engineering Leader’s Field Guide to the Leadership Paradigms AI Is Exposing
Chapter 1 of Come Prepared to Die. Someone will soon offer your service as software. The old you will have to die along with the way you provide your service today.
Invisible paradigms and a practice that survives
Chapter 2 of Come Prepared to Die. You decide through your paradigm, not with it, so you can't see it. The practice that makes it visible: the mirror, the Immunity Map, and the double-loop move.
AI as productivity layer vs AI as impetus for org redesign
Chapter 3 of Come Prepared to Die. Is AI a productivity layer you bolt onto the org you have, or the reason to redesign it? The cheapest mistake is the wrong tool; the expensive one is the wrong org.
Utilisation vs flow
Chapter 4 of Come Prepared to Die. Keeping everyone busy feels like good management. In knowledge work it quietly makes the whole system slower, and the maths takes five minutes to teach.
Espoused theory vs theory-in-use (Model I vs Model II)
Chapter 5 of Come Prepared to Die. The gap between what a leader says they value and what they do under pressure is the one axis you cannot self-diagnose. Here is how to close it.
Pushing people vs changing the conditions
Chapter 6 of Come Prepared to Die. The behaviour you keep failing to install isn't a people problem. It's punished by a loop in the conditions you designed. Stop pushing; change the loop.
Plan as commitment vs plan as hypothesis
Chapter 7 of Come Prepared to Die. When plan and reality disagree, most leaders load one reading: someone didn't try hard enough. The other says the plan was a hypothesis and the gap is data.
Local optima vs system constraint
Chapter 8 of Come Prepared to Die. Improve every part and you can still wreck the whole. Performance is not the sum of the parts; it is set by the one constraint that governs the system.
Output vs outcome
Chapter 9 of Come Prepared to Die. You shipped more this quarter than last, and your customers are no better off. Which number is the work actually being judged on?
Attached to outcome vs attached to inquiry
Chapter 10 of Come Prepared to Die. You defended a decision after it failed. But the decision was a hypothesis, and a hypothesis that fails is data. What you ultimately defended wasn't the decision, it was your identity. Reading the result and protecting yourself are two different jobs, and the second one eats the first.
Just This
Every framework in this book is a tool for contact with what is, and a trap the moment you obey it instead of using it.
Socialised vs self-authoring vs self-transforming
Chapter 12 of Come Prepared to Die. Robert Kegan's three developmental stages, and the capacity that lets a leader disagree with a confident voice, including an AI's.
Analysis vs recognition
You list five options, score them against criteria, and pick the highest scoring. The experienced operator already knew what option to choose, their skill long since dropped below conscious thought. You're slower and you're no more accurate. Nothing is wrong with the analytical method; it was simply aimed at the wrong decision. Chapter 12 named [...]
Your AI transformation will fail the way your Agile one did
Nearly nine in ten change programmes fall short of what they set out to do. Your AI transformation is being set up to join them, and the reason has almost nothing to do with the technology. A bonus edition of Come Prepared to Die, outside the numbered chapters. Look squarely at the last big change [...]
Deviation vs conditions
You're looking for the deviator who failed. The deviator was doing what the system trained them to do. Bainbridge's irony from chapter 13, that automation hollows out the operators it relies on, runs into incident response next, where blaming the operator leaves the conditions that produced the incident untouched. 🎧 Prefer to listen? This chapter [...]
Safety as absence vs safety as presence
The incident counter your team reports up is at zero. What it can't show you is how the work actually gets done safely and how to keep it that way. Chapter 14 walked through the anatomy of incidents. This chapter turns to what gets counted, because the safety metric you use decides what gets funded. [...]
Batch and push vs single-piece and pull
You set WIP limits and they're being ignored. Your batches are getting larger. Your lead times are getting longer. The PMO says everything’s fine. Chapter 15 closed the safety cluster. This one returns to the work itself, where most planning still gets batch size wrong and pushes work onto teams beyond their sustainable capacity. 🎧 [...]
Leader-follower vs leader-leader
You spent Tuesday in approval meetings. You spent Wednesday wondering why your team can't make a decision without you, and why the function still can't ship faster. The structure is leader-follower, all the way down. Chapter 16 named the discipline of small batches and pull. This chapter asks who holds the authority to decide what [...]
Theory X vs Theory Y
Chapter 18 of Come Prepared to Die. Your values slide says you trust your engineers; your approval process needs four signatures over $500. Your team is reading the signatures.
Expert vs facilitator
Chapter 19 of Come Prepared to Die. You're the last word on the technical call. You're also the bottleneck on every material technology decision. Both are true.
