Developer creates stress leaderboard using WHOOP to rank which coworkers raise his heart rate most

Developer Uses WHOOP and AI to Track Coworker Stress Levels

Developer Pankaj Tanwar has built a system that identifies which colleagues trigger the highest stress responses during his workday, creating what he calls a personal stress leaderboard 1

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. By combining data from his WHOOP fitness tracker with his work calendar, Tanwar developed a dashboard that ranks coworkers based on how much they appear to elevate his heart rate during meetings. He shared the experiment on X, posting a screenshot of the leaderboard while keeping identities hidden, and the post has already garnered more than 10 million views 2

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The project was powered by Claude's Fable AI model alongside custom code 1

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. To make it work, Tanwar reverse-engineered parts of the WHOOP system to access minute-by-minute heart rate data, something the wearable doesn't normally expose to users at that level of detail. He then cross-referenced those readings with Google Calendar events and attendee lists to identify which meetings consistently coincided with elevated heart rates 1

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How the Stress Leaderboard Works

The dashboard breaks down meetings using metrics such as heart rate increases, stress scores, and cumulative impact over time 1

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. The stress leaderboard doesn't just single out potential stressors—some coworkers appear largely neutral, while others are associated with calmer readings, effectively earning a reputation as the office's stress reducers. This transforms simple biometric data into an unexpectedly entertaining snapshot of workplace dynamics 1

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Tanwar used heart rate data analysis to match specific colleagues with physiological responses, though he acknowledges this isn't an exact science. Variables like a rushed walk to a meeting room, climbing stairs, an extra cup of coffee, or even a sugary snack could all raise readings 1

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. It's also possible that the subjects of the meetings are triggering heart rate spikes, rather than the coworkers attending them 2

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AI and Wearable Data Unlock New Health Insights

This experiment demonstrates what happens when wearable technology, coding skills, and AI converge to reveal patterns in everyday life that would otherwise go unnoticed 1

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. The use of Claude's Fable AI model to reverse engineer the WHOOP and extract detailed heart rate data showcases the increasingly capable AI models now available . Fable 5 has only just been released and is already being used to produce next-level apps and tools with just a few lines of prompting 2

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While the leaderboard probably isn't a scientifically rigorous measure of workplace stress, it represents a creative example of AI and wearable data applications beyond typical productivity tools 1

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. The data can still be used to manage health and well-being during the working day, in and out of meetings 2

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. This type of insight—identifying which colleagues cause stress, what parts of a commute are most stressful, or which activities promote calm—represents the kind of personalized health insights that AI-enhanced trackers should be delivering to users.