AI teams often think their biggest problem is the model. In practice, the bigger problem is alignment. If different people are optimizing different things, like accuracy, latency, recall, or edge cases, every experiment becomes a debate. One team thinks the system improved. Another thinks it got worse. High-performing AI teams avoid this trap. They agree early on what success looks like. Once that’s clear, experiments stop being arguments and start becoming progress. Learn how to build…