In late 2024, I started building an AI system to support my leadership.
It wasn’t as simple as opening a chat window. It took coding, custom logic, and far more trial and error than I expected. I spent three weeks over Christmas learning enough Python to build an early version and understand how it needed to work.
It was never about automating the job.
I built it to see whether AI could give me a clearer internal vantage point to hold the volume, pace, and complexity of my role as a CEO.
The moment it clicked came on one of those days when everything arrived at once.
Within the same hour, I was preparing for a board discussion, dealing with regulatory questions, and responding to journalists on a breaking story. Context switching was relentless.
I used an early version of Sage, my AI Chief of Staff, to pressure-test my thinking before stepping into each conversation. She didn’t give me answers. She stripped away noise so I could hold the line with more clarity and communicate with consistency.
Before that, my attention was fragmenting. I was coping, but at a cost. Each conversation made sense on its own, but coherence across them took real effort to maintain.
That day, something shifted.
AI stopped being a tool and became the basis of an intelligence system that could support how I actually work.
The Chief of Staff was one part of it. I also needed something to challenge my assumptions and keep me sharp on difficult days. That’s where the Performance Coach and Advisory Board came in.
Together, they became the early version of what I now think of as my AI leadership operating system.
As it evolved, I started using the term Executive Intelligence Engineering.
It’s the discipline of deliberately shaping how intelligence moves around a leader so clarity, judgement, and impact rise under pressure.
This idea sits at the centre of my upcoming book, EDGE. It’s a field guide for operating where pace is high, information is incomplete, and consequence is real.
What surprised me most is that you no longer need to code to build something similar.
You can now create a simple but powerful leadership operating system inside a trusted LLM by being deliberate about how it’s designed.
Here’s what shaped mine.
Start with the real work, not the tech
An AI leadership OS begins by understanding where your work gets heavy.
I wrote down the parts of my role that scattered my focus or slowed decision-making. That list became the design brief.
The work, not the tool, sets the architecture.
Make your leadership cadence explicit
Every leader has a rhythm, whether it’s written down or not.
I had to name how I prefer information, the principles that guide my judgement, when I need to slow down, and when pace matters. That context became the ground the system operates on.
Without this, AI amplifies noise. With it, AI reinforces clarity.
Design for roles, not one voice
Different parts of the work need different forms of support.
The Chief of Staff carries structure.
The Performance Coach holds consistency and energy.
The Advisory Board creates distance and challenge.
This is where AI starts to enhance human capability rather than flatten it.
Set rules that hold under pressure
The rules were simple, but non-negotiable.
Pause first.
Ask clarifying questions.
Frame the issue.
Explore options.
Weigh trade-offs.
Land the next step.
Consistency mattered most on the days when nothing else felt consistent.
Apply it to real work
The system only became useful once I trusted it with real decisions.
Board preparation.
Complex conversations.
Strategy notes.
End-of-day reflection.
I learn continuously, and the system learns alongside me.
What I’ve learned through this process is that AI should expand human capability, not narrow it.
Leaders who design how intelligence flows around them can carry more load without losing coherence. Those who don’t risk being pulled apart by pace, even while performing well on the surface.
That’s why Executive Intelligence Engineering matters.
Not because of the technology, but because judgement is now the scarce resource.
To the edge and beyond. See you out there.
Kate