While big models captured all the early glory with their larger context windows, greater parameters and more power, the reality on the ground for many enterprise engineering teams has gotten increasingly frustrating. Scale alone felt like it would generate intelligence, but most AI projects still feel like prototypes because the industry chased model size at the expense of the real bottleneck, retrieval.
We’ve reached the stage where enterprises need accuracy over novelty, with an AI strategy that uses the information they already have…
