Lagrange's proof network often faces a dilemma in production: either fast but expensive, or cheap but slow. The solution is not either-or, but to introduce 'adaptive batch strategies and multi-path routing'. The key to batch strategy is not that the larger the batch, the better, but to find the balance point between unit cost and tail latency; the key to routing is not that the more paths, the better, but to let queue depth, end-to-end latency, and unit cost become routing signals, automatically switching between low latency and low cost, while leaving a degradation path to ensure user experience through delayed verification during anomalies.
In engineering, degradation and recovery must be written as parameterized scripts: trigger thresholds, what mode to fall back to, how to label temporary storage and re-verification, when to return to normal. Before going live, conduct anomaly injection testing on sample data to ensure that state consistency is not compromised during data delays, network congestion, and computational hotspots. After going live, adhere to minimal change fixes to avoid large-scale strategy switches during periods of pressure. The ultimate goal is to make 'I have verified' the default, rather than an expensive ritual.
When unit economics improve with scale, interoperable interfaces stabilize, and degradation scripts become replicable, verification will transition from concept to habit. Once a habit is formed, debates will return to facts, and attention will shift back to creation itself.
