Jul 28, 2026

AI Agents for Performance: Ship Faster, Pay Less — Rajat Shah, Netflix

Rajat Shah details Netflix's approach to automating performance engineering using AI agents. He describes how an agent can read production profiling data, identify quadratic inefficiencies, propose code fixes, and validate them via canary deployments. The talk highlights the importance of a shared anti-pattern catalog and shifting from reactive bug fixing to proactive prevention by integrating AI early in the development cycle, emphasizing foundational automation and structured autonomy levels.

Mar 11, 2026

Why AI Engineers Need to Understand GPU Hardware (with Chris Fregly)

Chris Fregly, author of 'AI Systems Performance Engineering', explains that true performance gains in AI come not from raw compute but from a deep, holistic understanding of the entire hardware and software stack. He emphasizes that memory bandwidth is the most critical GPU metric and introduces the concept of 'mechanical sympathy'—the co-design of hardware, software, and algorithms—as the key to unlocking efficiency and overcoming modern bottlenecks.