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SPY Sentinel AI
SPY Sentinel AI is an Alpaca-connected SPY options paper-trading agent built around two separate authorities: evidence authority and promotion authority. Evidence authority asks whether market evidence is trustworthy enough to become learning. Promotion authority separately asks whether that learning has been independently validated enough to replace the Champion. The system observes live SPY and current options data, evaluates TRADE/NO-TRADE opportunities, applies deterministic contract and risk gates, can execute approved Alpaca paper trades, monitors positions and exits, and preserves an auditable decision trail. SPY Sentinel also records outcomes and counterfactuals and audits the evidence itself. During live-market collection, an earlier collector contained fresh SPY prices but option context inherited from an older audit whose freshness could not be independently proven. The system did not rewrite history. It preserved those records, quarantined the questionable component, excluded it from clean learning, and corrected collection prospectively with independently timestamped Alpaca option quotes. The intended proof chronology is: Decision ID → evidence timestamp → decision and gates sealed → Alpaca paper order submitted → fill/exit. This makes pre-execution reasoning distinguishable from hindsight reconstruction. Qualified evidence may make a Challenger training-ready, but the Challenger cannot self-promote, gain execution authority, or replace the Champion without independent validation. No live-money trading is enabled. SPY Sentinel does not claim that a profitable edge has been proven. Paper outcomes are observed paper results, not by themselves proof of repeatable edge. The system is designed to govern both what is allowed to teach it and what learning is allowed to change production behavior.
4 Sep 2026
