This article highlights the hidden complexity of scaling social features. It demonstrates how machine learning and platform-specific user behavior analysis are critical for delivering personalized experiences to billions, proving that simple UI often masks deep engineering challenges.
On its face the new Friend Bubbles feature looks simple enough. It highlights Reels your friends have watched and reacted to. But sometimes the features that seem the most straightforward require the deepest engineering work.
On this episode of the Meta Tech Podcast, Pascal Hartig chats with Subasree and Joseph, two software engineers from the Facebook Reels team, about what it took to bring Friend Bubbles to life. They discuss the evolution of the ‘ machine learning model behind the feature, the different behaviors between iOS and Android users, and the surprising discovery that finally made the whole feature click.
If you’ve ever underestimated a “simple” feature, this one’s for you.
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The Meta Tech Podcast is a podcast, brought to you by Meta, where we highlight the work Meta’s engineers are doing at every level – from low-level frameworks to end-user features.
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The post Reel Friends: Building Social Discovery that Scales to Billions appeared first on Engineering at Meta.
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