Ideas · The AI Office
Not a feed of tools. A working office: how I think with AI, how I build with it, and how I decide when not to.
These are the frameworks behind using AI properly. See how that becomes work.
The stance
Then, if AI helps us solve the problem faster, better or differently, we use it. If it does not, I say so, and we do the thing that works instead. That is the whole position, and it is a rarer one than it should be.
Most of the AI conversation I hear in boardrooms is a conversation about tools. Which model. Which vendor. Which pilot. The smartest leaders I speak to are not trying to become AI experts. They are asking a smaller and much harder question: what does this change about how we decide, what we own, and what we no longer need to be good at ourselves?
AI is an accelerant and a capability. It was never the point.
So the questions in this office are not about features. They are about leverage:
How I think with AI
These are not products. They are the shapes I use to think, and I am sharing them because a good frame is worth more than a good tool.
Framework one
Most people are standing on the first rung and calling it the whole ladder.
Every rung is a different relationship with the technology, and a different kind of value. The higher you climb, the less it looks like using a tool and the more it looks like owning a capability.
Framework two
One model is an assistant. A directed set of models is a team.
Stop asking which model wins. The interesting move is to stop choosing one assistant and start designing an AI team, with distinct roles, a critic that is not the author, and a human who decides. The loop is the same whether it runs on Claude, on ChatGPT, or across both.
Framework three
If intelligence becomes rentable, what becomes valuable?
Foundation intelligence is now something you rent, by the token, from a handful of suppliers, and your competitor rents exactly the same. So the advantage cannot live there. It moves to what only you have: your context, your memory, your workflows, your rules, your judgement, your customers, and the way your people actually make decisions. Value moves to what only you know, and to how well you own it.
What you rentReasoning. Language. Pattern recognition. Speed. Breadth. Everything a large model does the moment you ask, from whichever provider is best for the job this year.
What you ownYour organisational memory. Your proprietary context and data. Your workflows, permissions and rules. Your institutional knowledge. Your customer understanding. The way you evaluate good from bad. The way your best people decide.
Privacy matters, and it is one dimension of this, not the whole of it. Ownership is the wider idea: knowing what is yours, keeping it in a form you control, governing who and what may act on it, and being able to plug it into any intelligence you choose to rent, without being captive to one.
The businesses that win this decade will not be the ones with the best model. They will be the ones whose own context is the best organised, the best governed and the best connected to the intelligence they rent.
Built, not described
I work directly in the Claude and OpenAI APIs and have designed, shipped and run AI platforms of my own. So when I say something can be made to work, that is not a slide. It is something I can prove by building it.
Rare diseaseraretrial.org
What I sawHalf a million clinical trials existed in public, and the patients they were written for could not read a word of them.
What I builtA search engine that turns 500,000+ trials into plain English, on 10,900 disease pages families can actually use.
JudgementThe Roast Council
What I sawAI agrees with you. That is pleasant, and it is exactly the wrong thing when you are about to spend real money on an idea.
What I builtA hostile council that argues with your idea from six directions before you commit to it. The Orchestration Loop, running.
Childrencaptaincleo.com
What I sawChildren will need money, maths and AI fluency, and almost nothing teaches all three without feeling like homework.
What I builtA galaxy of games where the learning is the play, with no ads and nothing sold to a child.
This sitemaheshika.com
What I sawMost advice about AI is delivered on websites that could not have been built with it.
What I builtEverything here, designed and built with the same methods I describe.
The pattern is always the same: I see something, then I build something. The building is how I know the seeing was right.
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Selective advisory for leadership teams and boards, and speaking for the rooms where these decisions get made.
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