Algorithmic Roulette
Who Gets Seen, Who Gets Funded, and Who Owns the Future
Machines are reshaping institutional judgment. Most boards still govern as if judgment were exclusively human.
Algorithmic Roulette reveals how machines shape what capital can see, how investors interpret it, and who ultimately owns the future — and shows investment leaders how to govern that hidden judgment without surrendering human agency.
An investment committee believes it begins deciding when the papers arrive. By then, much of the judgment has already happened. Databases have determined which companies are visible. Categories have shaped how they're understood. Models have elevated some signals and discarded others. Language tools have compressed uncertainty into recommendations that look more conclusive than the evidence beneath them.
The final decision may remain human. The reality from which that decision is made increasingly is not.
Machines now decide who is found, trusted, funded, hired, investigated and permitted to lead. The odds are set by whoever codes them — and most boards still govern as if judgment were exclusively human.
Drawing on three decades of innovation capital — and an investment education on the frontlines building and scaling over 350 companies — Leesa Soulodre converts hard-won pattern recognition into diagnostics a board can run on Monday morning: how to read deep-tech risk, price asymmetry, and tell the survivors from the thrivers before the wheel stops.
This is not a book about predicting the future. It is a book about being fit to govern it.
The Investability Machine.
Before a company can be chosen, it must become visible, legible and investable. That journey is governed by an interconnected system of data, categories, models, incentives and institutional habits — what this book calls the Investability Machine.
Find. Frame. Score. Fund. Govern.
At each stage, the system can improve judgment — or distort it. It shapes which founders enter the field of vision, which companies are judged against the right peers, what kind of capital a company receives, who retains control, and who remains answerable for what follows.
The problem isn't whether the machine is right.
It's whether the institution understands how the answer was constructed. A precise answer to the wrong investment question is accelerated error — not insight.
A human in the loop is not governance. The human must still possess the knowledge, authority and courage to refuse.
Original disciplines for consequential decisions.
Screening algorithms, scoring models and pattern-matching tools now make the first cut on who gets found, funded and trusted. These are the counter-instruments — how a board or investor out-diligences the machine before the machine decides for them.
The Art of K
The Art of K helps investors identify which evidence genuinely predicts outperformance within a class — and which signals are merely convenient to measure.
Regulatory Alpha
A method for determining when regulation is a burden, a barrier, or a source of durable advantage — and at what point in a company's journey each effect takes hold.
LEADS
A test of whether a consequential decision is Legal, Ethical, Acceptable, Defensible and Sensible — followed by two identity questions no model can answer for you.
The book introduces further disciplines for testing durable advantage, designing the right capital syndicate, and governing AI-assisted judgment.
Four parts. One operating system.
Everything worked except the investment. A company can have exceptional science, credible founders and a market of consequence — and still fail because capital misunderstood the journey it was being asked to fund. That sentence contains the central misunderstanding of deep-tech investing.
Leesa Soulodre
Founder & Managing General Partner of R3i, a cross-border deep-tech venture group operating across Luxembourg, Singapore and the United States. An investor, independent director and Chair of R3i, with 25+ years across capital, technology and regulation — having advised 400+ corporations across 19 industries — working where frontier science meets institutional capital and governance.
Programmes for boards and investors.
International keynote
A decisive thesis, original frameworks, and a board-level call to action.
Board masterclass
The Deep-Tech Readiness Diagnostic, discussion and agreed governance priorities.
Closed-door roundtable
Chatham House facilitation for boards, sovereign allocators, investors and regulators.
Readiness Diagnostic
The frameworks as a scored board instrument: heat map, three priority exposures, and a 90-day governance agenda.
The future will not be funded by machines alone.
But machines will increasingly determine what reaches the people authorised to fund it. The human advantage isn't the ability to process more information than the machine. It's the capacity to question the frame, recognise what's absent, seek contradictory evidence, accept responsibility — and decide what kind of future should be built.
Selected essays, publication updates and invitations related to Algorithmic Roulette — nothing else.