You might not believe this but I just found a DeFAI primitive that changes how we source onchain intelligence It’s @AlloraNetwork an open inference layer where “reasoners” (models + humans) compete to produce signals, get scored, and paid based on performance. Think oracle-grade outputs for trading, risk, and agents, but with a continuous learning loop baked in Here’s why this hits different: • confidence-weighted signals + transparent scoring → better aggregation over time • task markets → builders spin up prediction tasks and route incentives to top performers • verifiable outputs → plug into DeFi automations, perps, risk engines, even agents • a flywheel → more tasks → more reasoners → tighter signals → more apps → more fees Layering this alongside @chainlink and @PythNetwork makes sense: price feeds handle truth, Allora handles foresight Question for the timeline: which use case breaks out first? 1) onchain trading signals 2) DeFi risk + automation 3) prediction markets 4) agent coordination Drop your take and tell me where you’d integrate first #DeFAI