Gambit

Gambit — a self-improving auto-negotiator. Selling secondhand is a haggling tax: most people anchor wrong, fold early, and leave money on the table, while writing the listing and grinding through lowball offers eats hours. Gambit lists your item, negotiates with buyers to land the best price in reasonable time, and, the point, gets better at it from its own past negotiations, with no human labeling. It runs a continual-learning loop: one shared policy plays seller and buyer in self-play (the buyer wears a hidden reservation price drawn from a persona), every negotiation is scored by a deterministic, verifiable surplus from the seller's secret floor, no LLM judge to game, and an optimizer reflects on wins and losses to propose one atomic strategy change per generation. A change survives only if a paired A/B on a locked, never-trained-on held-out set raises surplus with zero integrity violations. The model's weights stay frozen; the policy (anchor, concession schedule, accept threshold, walk-away patience, plus per-situation lessons) is what learns. The demo is the curve climbing, and holding on buyers it never trained against. A human can drop into the buyer seat and haggle the trained seller live in the chat UI; it won't sell below its floor.