Prediction systems often assume that market signals converge naturally toward accuracy. In practice, convergence is shaped by how exposure and resolution are structured. @Solstice_TG $SLX frames outcomes through structured liquidity, where capital commitment influences signal strength over time. @useTria $TRIA introduces execution pathways that allow positions to persist even as context shifts. @intodotspace $SPACE, as a prediction market, highlights how early positioning can anchor later expectations before sufficient information emerges. These systems suggest that prediction accuracy is not only a function of information quality, but also of temporal exposure and resolution mechanics. Signals may stabilize not because uncertainty is resolved, but because participation becomes asymmetrically costly. A technical question follows: in prediction driven architectures, should market design explicitly account for temporal anchoring effects, or is signal stabilization an acceptable proxy for informational certainty as system complexity grows?