Who's on call? How Claude helped us calculate this 2,500x faster

The text discusses the challenges and improvements made to an on-call schedule rendering system to enhance its performance and efficiency. Initially, the system faced significant CPU usage issues due to complex calculations required to determine on-call staff, which involved iterating through historical and future schedule entries. Various optimization strategies were employed, such as analyzing flame graphs, implementing validation checks, and enhancing code efficiency through methods like binary search and caching. Despite initial setbacks, including a bug related to daylight saving time and overlapping schedule entries, the integration of AI tools, particularly Claude Opus 4.6, facilitated substantial improvements. The AI provided innovative solutions, such as fast-forwarding time calculations and more efficient user allocation algorithms, which reduced the schedule rendering time significantly. As a result, the schedule API response times improved dramatically, exemplifying the successful application of AI in streamlining complex operational processes.

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