continue to struggle with one of the most fundamental challenges in AI: How can I know when a cheaper model is sufficient for a task? I asked a friend, Leo Zheng, who leads marketing for Fireworks AI, an AI infrastructure company that runs and improves open-weight models. Fireworks, he said, wants to “enable every company to own the continual learning loop within their four walls.” I was asking how to automate model choice, but the harder problem is building a feedback loop that tells a company what worked. Arguably, the more important component is integrating enterprise data into that continual learning loop that Zheng describes.