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Engineering at Meta

Meta’s AI Storage Blueprint at Scale 10 Years of Meta’s Commitment to Python Privacy-Aware Infrastructure in the AI-Native Era: An Asset Classification Case Study How Meta Engineered Ultra-Narrow Batteries for AI Glasses Adopting AV1 for Real-Time Communication (RTC) at Scale Lights Out, Systems On: Validating Instant Power Loss Readiness SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems Migrating Data Ingestion Systems at Meta Scale
Reel Friends: Building Social Discovery that Scales to Billions
By Pascal Hartig · 2026-05-13 · via Engineering at Meta

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.

Download or listen to the episode below:

You can also find the episode wherever you get your podcasts, including:

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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