Designing an AI serving harness built to last
TL;DR
The next competitive advantage in enterprise AI depends less on which model a company chooses than on what it builds around it, MIT Technology Review argues. For several years the AI conversation centered on model capability: bigger models, better reasoning, larger context windows and higher benchmark scores. The piece makes the case that the serving layer built around the model is becoming the part that decides whether enterprise AI holds up over time.
Nauti's Take
Investing in a clean serving layer gives a real advantage: models can be swapped without rebuilding the whole workflow. The risk is overbuilding, since complex routing costs maintenance before it pays off.
Small teams do best starting with a swappable provider, logging and cost limits for one real workflow.
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