Session Details
Measuring the Impact of AI on Developer Productivity at Meta
With AI adoption at the forefront of developer productivity investments across the industry, the question of how to measure ROI is dominating discourse. At Meta, we’ve established a comprehensive suite of metrics that measures the impact of AI on developer productivity.
In this session, we’ll describe the extensive telemetry we have created to support this, explain how to handle complex source control operations, and share directional correlations with more classic developer productivity metrics.
By the end of this talk, you will understand how Meta has approached AI driven developer productivity all the way from adoption to the value it adds to our business.
meet the speakers
Pavel Avgustinov
Pavel Avgustinov is tech lead for the Developer Products org at Meta, where he spends most of his time assisting AIs in assisting engineers. His work spans from foundational compiler research at Oxford University to building practical semantic analysis tools at scale, with a pervasive focus on developer tools and productivity. At GitHub, he led GitHub Advanced Security, as well as the teams building code search and navigation over hundreds of millions of repositories.
Payam Shodjai
Payam Shodjai is Product Management Director for Meta’s developer infrastructure, where he spends most of his time applying AI to the software development process. He started his career as an engineer at Microsoft, working on developer tools, before transitioning to product management at Google, where he worked for 15 years on Google Search, Ads, Assistant and Gemini.