Summary

Weta's chief AI officer and head of product management introduce an open-source context platform engineering toolkit designed to optimize AI agent performance. The toolkit features a load generator that enables configuring agent swarms, model parallelism, and memory tiering options, with a key focus on maximizing key-value (KV) cache hit rates for production-grade AI agents. Drawing insights from the Manis context engineering blog, the team emphasizes the importance of addressing "token anxiety" and eliminating token rate limits to improve software development productivity. The open-source toolkit is available on GitHub, and the presenters encourage developers to download, experiment with, and contribute to the project to advance the field of context platform engineering.