Wiring, Energy, and Why AI Actually Helps
I was diagnosed with ADHD late in life, which was useful not because it changed anything about who I am (spoiler: it didn't) but because it finally explained the energy cost of being who I am; and more importantly, why that cost is so invisible to everyone except me.
A lot of the things I get consistently praised for (great in emergencies, high energy, big picture thinking, lots of ideas) turn out to be ADHD traits.
So do the things I quietly struggle with: grinding repetitive work, maintaining consistent output when nothing is on fire, losing an entire complex train of thought because someone pinged me about a meeting.
Here's the thing people get wrong about this: there’s no superpower here, no easy silver lining to neurodiversity. It's a trade-off I didn't choose, and most of life is the boring 80%, not the dramatic 20% where I shine.
So what actually helps?
AI tools have given me something I didn't expect when I started using them properly: sustainable cognitive load management (which sounds like corporate wellness nonsense but bear with me). Not more productivity. Not a shortcut. Just a way to spend my finite and unevenly distributed energy on the things that genuinely need it.
What does that look like in practice?
The blank page problem
I had a large-scale rework to plan for our dashboarding platform. It sat on my to-do list for four weeks.
Talking it through with an AI inside the codebase meant the plan developed in context, close to the actual work, not in a note I'd definitely never find again; and it covered the gaps in my knowledge of Python specifics and infrastructure detail that would have slowed me down anyway.
The house of cards
Complex technical thinking is a bit like building a house of cards; carefully constructed, very satisfying, and completely vulnerable to the first interruption.
Context switching knocks it flat and you start again from nothing (this is exhausting in a way that's very hard to explain to people who don't experience it). Keeping an AI conversation thread alive means the house is still standing when I come back, even after a meeting, a call, or just needing to step away and actually recharge.
Thought parking
Interesting conversations always generate more ideas than I can develop in the moment; and the energy to develop them arrives with the idea, not later when I have time.
I stub them out as AI threads, enough to be useful, and they sit there waiting. The result is that I'm rarely saying "I haven't got to that yet." I say "I have some preliminary thoughts on that actually" — and in a leadership context, that difference is not small.
The T-shape tax
Staying genuinely broad across engineering, delivery, data, infrastructure, and everything else leadership requires is expensive - AI holds the horizontal bar of the T so I can spend my depth-energy deliberately rather than just reactively filling whichever gap is most on fire today.
AI doesn't fix ADHD (nothing fixes ADHD, that's not how it works). The integration gaps in enterprise tooling are real and genuinely frustrating; I want my Slack and my Teams and my Code to have contextual awareness, but the tasks where AI would help most are often the ones locked behind a wall of manual copy-pasting. And a faster rabbit hole is still a rabbit hole. But for managing the energy cost of staying high-functioning across a complex role, it's the most useful thing I've found.
Did I use AI to help write this? Of course I did. And it's better for it.
Graffiti image of a sign directing to Utopia, found in Florence, Italy.
