Building SDKs in the Agentic Era

In the time it takes to train a frontier model, the open source libraries we rely on can undergo significant changes. This creates an ongoing delta between what an LLM coding agent suggests and what the best practices are, or what even works. For the team at Google DeepMind, this is an ongoing challenge as we publish both models and open-source SDKs.

This talk will share some of the challenges that we, as SDK maintainers face, and we'll share some results from our experiments. We'll focus primarily on the "training cutoff knowledge gap", and how it is applicable for users and owners of open source projects, but we will also discuss some of the other challenges maintainers face in a world where producing code is trivial.