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Multi-Surface Behavioral Retention Telemetry — Cross-Surface Return Mechanics

The MULTI-SURFACE outcome has 2 of 3 required surfaces live (Product.ai Website + ChatGPT App), with Desktop Extension Research Mode shipping and Mobile App next-zone. The outcome's value rests on a load-bearing assumption from the productai-kernel A-2 (intelligence is multiplicative across three domains) and brand-kernel A-4 (installable surfaces converge under utility physics): a multi-surface product compounds retention because users who experience verdicts in one surface return through another. Today nobody knows if that is happening. There is no cross-surface user-continuity measurement. There is no "did users come back" measurement on any single surface. The Trust Paradox (74% rate verified-truth assistants 4-5/5 on trust; 93% verify before transacting) means that surveys will report "yes I'd use it again" while behavior shows "no I didn't" — and the team is currently optimizing on stated trust without behavioral telemetry. If multi-surface fragments retention rather than compounding it, the entire surface-fleet thesis is wrong; if it compounds, knowing which surface drives the highest return-rate determines where Product.ai invests next. Without measurement, the team is shipping surfaces blind.

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