Make the next model swap boring
EXL's sponsored piece in MIT Technology Review makes a point pilot teams should hear early. A model swap should be an evaluation and configuration decision rather than an architectural reset. I'd carry that into governance. Sitting on an AI approval committee taught me that reviews drag when nobody has written down what the workload actually requires, so every new model feels like starting from zero. If your latency and cost targets live in a document and your evals run against them, approving the next model gets pleasantly boring. Can your team say today what would make a cheaper model good enough?
Source: Designing an AI serving harness built to last (MIT Technology Review)