foresight machines

foresight machines

ManifestoThe future should be engineered with foresight

Simulate what could happen. Discover what could work.

Foresight Machines model the financial and physical systems behind every commitment, project how they could unfold, and find better ways to allocate capital and coordinate resources.

Discuss a decisionSee how it works

Mission

Expand what we can responsibly make possible.

There’s forecasting, and there’s foresight.

Forecasting anticipates the conditions ahead, and machines now do it about as well as the best people.

But every commitment sits inside a system larger than the decision itself: other participants, agreements, constraints, and the conditions they meet. The outcome turns on how they move together.

Today those systems are modeled on spreadsheets, one scenario at a time.

Foresight runs the whole system forward, then searches for a better arrangement: a different allocation, new terms, a sequence that makes a project possible.

Models like these took specialists months to build. AI is making them fast to build and practical to keep current.

  1. 01Dashboards

    Show what happened.

    You read them.

  2. 02Forecasts

    Estimate what is likely.

    You interpret them.

  3. 03Foresight Machines

    Simulate what could happen. Discover what could work.

    You set the goal and decide.

Where we start

Enough money, in the right place, at the right time.

Digital dollars move at any hour, through exchanges, wallets and payment networks. The cash behind them sits in funds and banks that keep their own hours. A Foresight Machine models that whole network, and finds where money should sit before it’s needed.

Where should the cash behind a digital dollar sit, and when?

Every account, route and partner, and the hours each one keeps.

IssuerMoney-market fundCustodianOvernight repoFintech appsExchangesWalletsPayment networksPartner banks

Domains

Wherever capital is committed.

Every domain gets the same three questions: what happens if conditions change, what changes if we act differently, and what arrangement could make this work.

  1. A bank tower on a vault plinth, linked by one lit route to a small cluster of partner kiosks.

    Reserves & liquidity

    Issuers, networks and funds that owe cash on demand

    1. 01What if partner balances grow 40% next year?
    2. 02Which bank should carry our weekend redemptions?
    3. 03What would let us redeem instantly, any hour?
  2. A ladder of stepped blocks of rising height beside a lender’s tower; the tallest step is lit.

    Credit & collateral

    Lenders and managers whose collateral moves with rates and prices

    1. 01What if rates stay higher for two more years?
    2. 02Which collateral should we post, and where?
    3. 03What terms let us lend where we decline today?
  3. A neighborhood of small houses and shops, all linked by fine lines to one lit data center.

    Risk & insurance

    Insurers writing new risks with little history: cyber, AI, digital assets, climate

    1. 01What would one provider’s outage cost across our book?
    2. 02Where should the trigger sit, and how should cover be layered?
    3. 03Could we cover a risk no one will write today?
  4. A solar field and a factory joined by one rail line; the rail link is lit.

    Projects & supply chains

    Developers and manufacturers whose plans depend on delivery

    1. 01What if equipment arrives six months late?
    2. 02More inventory, or a second supplier?
    3. 03What makes this financeable at today’s rates?

Method

A model to explore with. A record to improve from.

  1. A neat stack of documents and a ledger, glowing faintly at the edges.

    Evidence

  2. The white world model, assembled.

    Model

  3. The model with its fan of frosted futures behind it.

    Simulate

  4. Two futures side by side, one brighter.

    Compare

  5. One lit future, alone on a plinth.

    Decide

Simulation tests alternatives. Observations test the model.

Trust

Models earn trust against reality.

Every recommendation shows its sources, its assumptions, and how confident the model is.

  1. 01

    Built from evidence.

    Every rule traces to a record, a contract or an observation.

  2. 02

    Tested against alternatives.

    Every recommendation is compared with current practice, under the same rules.

  3. 03

    Kept current.

    The model changes as the institution does, and every version is kept.

  4. 04

    Corrected by outcomes.

    Every expectation is recorded before the fact, and every miss improves the model.

Manifesto

The future should be engineered with foresight.

Humanity has built extraordinary systems for recording the past and managing the present.

We are not building an oracle. We are building machinery for better judgment.

Read the manifesto