"Over a period of just about 5 years, the use of AI-based tools for software engineering has gone from being a very promising research investigation to indispensable features in modern developer environments. At Google, we have been developing and deploying AI-based tools to surfaces where Google engineers spend the majority of their time, including inner loop activities such as code authoring, review and search, as well as outer loop ones such as bug management and planning. Improvements in these surfaces are monitored carefully for productivity and developer satisfaction.

This talk will present AI-powered improvements and continuing transformation of Google’s internal software development. We will touch upon the challenges in how to align our internal efforts with the very fast moving field of LLMs, and what challenges we have faced to bridge the gap from research to real products with usage at scale. We need to constantly make judgment calls on technical feasibility, the possibility of iterative improvement and the measurability of impact as we decide what ideas to pursue for production level adaptation and adoption. The talk will go into several examples of this that we have gone through in the recent past, and what we have learned in the process.

We will demo some of the generative AI based projects for software engineering at Google. In particular, we will show how we weave a conversational agent in an IDE, which combines convenient workflows for information gathering, conversations about code, and code transformation abilities.

We will conclude the talk with a discussion of opportunities we see for the next five years and some thoughts on how the community can collaborate better by focusing on good benchmarks."