I’m building Decision Intel: AI that audits the reasoning behind your biggest decisions, and catches the blind spots before the committee does.
I’m 16, raised between Lagos and the UK. For the last few years I’ve chased one question: why do smart, well-resourced people get important calls so wrong? Everything below is me putting the answer under pressure, as a company, as research, as teaching.
This is what Decision Intel does, in miniature. Here is a recommendation that looks airtight. Switch on the biases hiding inside it and watch the conviction, and the quality of the thinking, come undone.
Proceed, high conviction.
Nothing flagged yet. Toggle a bias above and the audit surfaces it here.
This is Decision Intel, in one tile, but it runs on real strategic memos, not a toy.
One question has followed me into everything: why do smart, well-resourced people get important decisions so wrong? I don’t think it’s a lack of intelligence. Good reasoning has to be built and pressure-tested, not assumed, and most of the time nobody does the building. The mistake is already in the thinking long before it shows up in the result.
But I’m not content to just diagnose it. When I see a flawed way of reasoning, my instinct is to build the system that catches it, and ship it. Decision Intel and Sentinel are both that instinct made real: full products, built end-to-end and solo, put in front of real memos and real markets instead of left as ideas. I’d rather pressure-test a thing in the world than perfect it on paper.
And that instinct isn’t tied to one place or one field. Raised between Lagos and the UK and headed for San Francisco, I think in global markets by default. The thread running through the company, the research, the teaching, and a live trading desk isn’t finance, or psychology, or code. It’s the quality of the thinking underneath all of them.
Most of us never audit our own thinking. We just trust it, and find out later whether we should have.
Find where smart people reason badly, and no one is checking.
In practice The 2008 paper started here: a crisis everyone blamed on the maths was really a failure of minds.
The same cycle, whether the thing is a company, a paper, or a classroom.
The same obsession, how people reason and decide, pursued as research, as companies I’ve built, as teaching, and on a live desk.
A reasoning-audit platform. It reads a high-stakes strategic memo and surfaces the cognitive biases, blind spots, and weak assumptions in the reasoning before the decision gets made, not after the outcome punishes it. I built it because the most expensive mistakes I kept reading about weren’t failures of data; they were failures of thinking that no one checked.
An autonomous market-intelligence platform built on a multi-agent AI architecture. It doesn’t just flag what moved, it argues why, runs every thesis past an adversarial “red team” agent that tries to tear it down, and calibrates its own confidence against its real track record. The same obsession as everything else here, turned on the market and on itself.
A published paper arguing the UK’s 2008 banking crisis (the run on Northern Rock, a full year before Lehman) was less a failure of maths than a failure of the human mind: bounded rationality, System 1 racing ahead of System 2, and the hormonal “Winner Effect” that biologically dials up a trader’s appetite for risk as the profits roll in. It’s where the whole obsession started.
A student-led initiative I co-founded to teach younger students how money actually works, and just as importantly, the psychology that quietly drives the decisions they’ll make about it.
Built and run with other students, because the fastest way to find out whether you understand something is to teach it to someone younger.
The same lens, applied to live markets: building a portfolio-intelligence view that makes a fund’s exposure, its risk, and the real drivers of its returns legible at a glance, so the people making the calls can actually see what they’re deciding on.
A portfolio-intelligence dashboard: exposure, risk metrics, and performance attribution, assembled into one view a manager can act on.
I was born in the United States and raised between Lagos and the UK. Lagos is home. San Francisco is where I’m headed next.
I’m sixteen, which I mention here, near the bottom, rather than at the top, because I’d rather the work spoke first.
Away from the screen, I’ve played piano for twelve years: ABRSM Grade 6 piano, Grade 6 guitar, and Grade 5 music theory with distinction. Practising something for years before you’re any good at it turns out to be the same discipline everything else here needed.
When I'm generally reachable. Term keeps weekdays busy; evenings and weekends are best.
Born in the U.S., raised in Lagos, building from London — San Francisco next.
Twelve years in: ABRSM Grade 6 piano, Grade 5 theory with distinction. Practising something for years before you’re any good at it turns out to be the same discipline everything else here needed.
ABRSM Grade 6 guitar, picked up alongside the piano. A different instrument, but the same lesson: the boring reps you put in long before anyone hears you are the whole game.
Six days a week, on a push-pull-legs split. It is the same kind of system as everything else here: small, repeatable, and built to run on the days I least feel like it. Discipline compounds.
Rated “Excellent” across quality of work, timekeeping, work relationships, and competency in role during a finance internship, cited for math and communication, and for being receptive to feedback. Objectives signed off as fully met.
I’m a Christian. It’s the quiet foundation under all of this — the reason I care about building things that are honest, not just clever, and the thing that keeps the work in proportion whether it’s going well or it isn’t.
“Trust in the Lord with all your heart, and lean not on your own understanding.”Proverbs 3:5
If any of this resonates, I’d love to talk. Naturally, I ran the decision through my own auditor first.
The lowest-risk decision on this page.
