P34 is a foundational decision model for computable markets. This page translates the technical thesis into plain language — without flattening it.
Everything P34 does is one loop, run with discipline.
| Concept | What it means |
|---|---|
| Business menu | The set of actions your business could take right now — deals to buy, loans to approve, loads to accept, offers to make — each with quantities, timing, counterparties, prices and constraints. |
| Context | What the market and your business look like around that menu: history, inventory, capital, seasonality, fees. |
| Decision model | P34 evaluates the menu as an economic decision problem, not only as a prediction task. The output is a decision, with predicted economics attached. |
| No-trade | Doing nothing is a valid output. When no candidate meets the model's criteria, P34 declines — a first-class, rewarded decision, not a failure mode. |
| Portfolio output | P34 selects actions and sizes them as one coordinated portfolio or workflow, so positions don't fight each other for capital or capacity. |
| Partial observability | The true market state is never fully visible. Operational telemetry — your realized outcomes — carries the signal that missing price discovery doesn't. |
| Controlled autonomy | The system can move from recommendation to execution — but only within user-defined limits and rollout stages. |
Language models reason, summarize, and advise. Ask one about a deal and you get an articulate essay — trained on text, scored on plausibility, accountable to nothing. Seven years of prompts won't change what the objective function rewards.
P34 is trained against realized economic outcomes — profit as the regression target (PARML). Ask it about a deal and you get a decision: take it at this size, or don't take it at all, with predicted economics it can be held to.
The two compose: your LLM agent talks to customers, reads contracts and orchestrates workflows — and calls P34 whenever a decision involves money. Seven years, not seven prompts.
Business history is biased: you only observe outcomes for the deals a previous policy already accepted. Models trained naively on that history become systematically optimistic — they inherit yesterday's enthusiasm and none of its regret. P34's model class treats declining to act as a rewarded output and controls false positives explicitly. In live operation, most of what P34 sees, it refuses.
Every candidate action is embedded with its context — including candidates historical policies never touched.
The model is penalized for confident acceptance of deals that would have lost money — not just rewarded for winners.
Survivors are sized jointly under constraints. If nothing survives, the answer is nothing — and that answer is respected.
Four stages from decision support to self-driving business. Toggle the view — the loop doesn't change; the stakes and the sign-off do.
You: read ranked menus, decide, act.
P34: scores and explains.
Controls: none needed — nothing executes.
You: approve each prepared action.
Your agent: assembles orders via the API.
Controls: per-action approval, budget cap.
You: review daily digests.
P34 + agent: execute approved action classes.
Controls: caps, drawdown limits, instant pause.
You: set the envelope, watch the P&L.
System: full loop within limits.
Controls: audit logs, drift monitoring, kill switch.
Stages labeled “Rolling out” / “Planned” are roadmap: planned, not guaranteed, and gated by market, controls readiness and legal review.