4 Engineering Patterns That Cut AI Inference Costs 60–80% Without Touching Output Quality

One of the most common engineering problems I see when teams scale AI from pilot to production: the cloud bill is 5–10× what the pilot suggested it would be. This isn't a coincidence or a billing error. It's the predictable result of pilot conditions not reflecting production conditions — cleaner inputs, smaller volumes, no monitoring overhead, no retry logic, no agent orchestration multiplication. Here are the 4 implementation patterns that fix it. All of them can be implemented without changin