In a randomized controlled trial, METR invited developers to complete 246 tasks. Despite believing AI improved their speed by 20%, these developers actually took 19% longer to finish tasks when using AI.

AI helps with specific tasks, such as pattern matching and report summarization, but in areas like performance engineering, experienced engineers can outperform AI due to their specialization and intuition. This highlights situations where human expertise still surpasses AI in complex problem-solving.

AI offers powerful capabilities, but it also introduces risks—especially for those not deeply familiar with the technologies involved. For example, it can be difficult to catch AI-generated code errors in unfamiliar programming languages, leading to time-consuming debugging.

To address these challenges, it’s important to reduce complexity. Instead of relying solely on AI-generated solutions, clarify business requirements and system architecture, and set clear boundaries for the AI’s output.

The METR study is a good read and poses important questions for our field. I encourage you to reflect on your own experiences with AI tools and consider how careful integration can shape better outcomes.

Happy Performance Engineering!

Read the study https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/

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