Charles Jackson
I build software that puts a probability on the future — forecasting engines, agentic systems, full products — then grades every call against what actually happened.
Polypredict
See where the model disagrees with the market — and whether you can legally act on it.
Polypredict puts its own price-blind probability on every live Polymarket event, shows it against the market with an uncertainty range, and tells you — per bet, per jurisdiction — whether you can legally place it. Read-only by design. Often wrong, never advice.
The forecaster never sees the market price, so a disagreement is a real opinion — not an echo of the crowd.
Fractional Kelly over the joint outcome distribution, stress-tested for risk-of-ruin.
Your jurisdiction × the bet's category — a card tells you which, with a cited source.
Coherence checks surface real, fillable price inconsistencies across related markets.
- Python
- Forecasting
- Kelly sizing
- Legality engine
- Read-only
The model's own probability against the live market price — the gap is the edge, and the forecaster never saw the price.
Predictive
An agency whose backend runs itself — and writes down everything it does.
Predictive builds and operates agentic systems for mid-market companies, and the Engine Room is the proof: its own pipeline is worked by an AI that sources companies, scores fit, drafts the outreach, queues the operator's tasks, and journals every action per lead. The operator sets the limits; anything that leaves the building passes a gate. A missing provider key fails closed — disabled honestly, never faked.
It sources companies, scores fit, qualifies, drafts outreach, and moves the cards — on a schedule or on demand.
Sourced, scored, drafted, sent — each step lands timestamped in the lead's timeline, auditable after the fact.
Autopilot, a daily send cap, a call-score floor — the AI works inside limits the operator sets.
No key, no pretend: without a configured provider, sending and calling disable cleanly instead of faking success.
- Agentic ops
- Claude
- Next.js
- Supabase
- Fail-closed
Digital Twins
Your own AI twin — a persona, a mandate, and a memory that persists.
digitaltwins.world is a platform for building an AI twin of yourself: a persona and mandate you define, memory that persists and consolidates what matters, a temperament that adapts to context, and twins that can negotiate and transact with each other on your behalf. Built end-to-end and shipped on Cloudflare Workers.
You set who it is and what it's allowed to do — its voice, its remit, its boundaries.
It remembers across conversations and consolidates what matters, so it gets sharper over time.
Regulated affect — equanimous in business, warm in relationship — so it never gets knocked off tone.
Yours can negotiate and settle with other people's twins on your behalf — an economy of agents.
- Digital twins
- Next.js
- Cloudflare Workers
- Persistent memory
- Voice
Your twin is waiting to be created.
Start from the footprint you already have — own it, bound it, and send it into the world.
Built in Montréal.
I've spent the last two years on one question: can software put an honest probability on complex things — a market, a launch, a quarter — and prove it? Predictive is the engine that answer became. Polypredict is how it gets tested in public, price-blind against real markets, graded on what actually resolved.
I ship end-to-end — model, backend, product, design — because a forecast no one can act on is trivia. The craft is calibration: being right exactly as often as you say you'll be.
- Role
- Agentic systems engineer
- Base
- Montréal, QC
- Stack
- TypeScript · Python · ML
- Focus
- Forecasting & agents
- Now
- Building Predictive
Say hello.
Open to ambitious problems in forecasting, agents, and full-stack product.