The Day the Treasure Hunt Engine Decided to Lie to Us About Latency
The article discusses the challenges faced by a team trying to improve the latency of a treasure hunt engine. Initially, their attempts to enhance perceived speed led to complications, including financial losses due to erroneous revenue reports. Ultimately, they reverted to a single database transaction approach, which improved latency but introduced new operational dependencies.
- ▪The marketing team aimed for instant feedback in treasure hunts to boost revenue per session.
- ▪Initial solutions led to increased latency and financial discrepancies, resulting in $87k in refunds.
- ▪The final architecture decision involved a single ACID transaction, improving latency to 15ms but sacrificing service independence.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3942477) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Lisa Zulu Posted on May 27 The Day the Treasure Hunt Engine Decided to Lie to Us About Latency #ai #machinelearning #webdev #programming The Problem We Were Actually Solving The marketing department wanted treasure hunts to feel instant. Not just responsive, but psychologically immediate—a sub-second confirmation that a chest was open, a key found, a prize unlocked. The CFO signed off on it because higher perceived speed meant higher revenue per session.
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