Presentation: Keeping ChatGPT Fast as AI Development Accelerates
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Presentation on keeping ChatGPT fast amid agentic workflows, covers performance costs and deployment strategies relevant to infrastructure.
OpenAI's performance engineering lead Martin Spier details how agentic coding workflows dramatically increase code change velocity, introducing hidden systemic performance costs beyond GPU bottlenecks. To counter this, OpenAI deploys always-on AI agents that automate profiling, regression detection, and continuous optimization, ensuring ChatGPT remains fast and scalable under massive global load. The talk emphasizes that the shift from human-reviewed to agent-driven development breaks traditional assumptions about change control, requiring new observability and platform engineering approaches.