How to Improve Agent Efficiency Through Context Engineering

This post details context engineering for analytics agents, focusing on improving efficiency and accuracy. It introduces four techniques: retrieval (warehouse metadata, endorsed tables), memory (previous analyses, published notebooks), institutional knowledge (workspace guides), and codified metrics (semantic models). It also addresses context rot through ground truth testing, trajectory evaluation, conversation-length trends, and token efficiency tracking, highlighting Hex's Context Studio for surfacing user questions and recommending context improvements. The post emphasizes that governed context moves accuracy more than model choice.