How to choose an AI model: lessons from Notion and Gamma

What this post added

This post introduces strategies for choosing and deploying AI models, emphasizing the importance of per-workflow model selection, the value of model switching for reliability and cost, the increasing viability of open-weight models, and the strategic use of fine-tuning for market growth rather than just margin improvement. It highlights the engineering cost and benefits of building flexible model harnesses and the use of A/B testing for subjective output evaluation.