Sitting in front of the screen, staring at BTC perpetual short positions, the market is highly volatile, but this time the position is unexpectedly stable. It’s not luck, but finally having reliable data support.

The biggest fear when trading is information lag. You can’t see the real situation clearly, only guess. Until one day, I checked on-chain data and discovered the oracle system. It’s not just talk; it’s genuinely being repeatedly queried and verified on-chain. In just a few days, it accumulated millions of query records, enough to prove that this system has moved from the experimental stage to practical application. It’s used in Bitcoin prediction markets and BTCFi contracts, directly affecting position settlement and involving real money.

Previously, the data foundation of BTCFi was very fragile. Besides price, other information was almost blank. Event outcomes and real-world status either relied on cross-chain bridges with severe delays or were simply unavailable. When market fluctuations hit real-world events, the system was prone to issues. In a BTCFi strategy linked to real events last year, delays in the oracle data feed directly triggered liquidations—that lesson was deeply memorable.

Later, I switched to an oracle solution that introduced an AI anomaly filtering layer. Let AI cross-verify data quality and intercept abnormal signals before on-chain submission. During volatile periods, stability was actually improved. This made me truly understand: oracles are not just data transmission pipelines but also a filter. They must block noise and distinguish signals.

From an architecture perspective, this system is like a precise machine. The outer layer captures raw data from the real world, the middle layer uses AI for cross-verification and anomaly detection, and finally, on-chain settlement occurs. Each step reduces risk. This design significantly improves the stability of the BTCFi market.