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  5. From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking
From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking
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From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking

Every day, Meta’s recommendation platforms handle billions of user interactions, generating rich temporal signals that capture individual preferences and intent across products, ads, and content. In our 2024 post on sequence learning for…

ArchitectureEngineering at MetaPublished: August 5, 2026
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The Agent Access Model

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How we built a software factory to drive Astro’s GitHub issue count to zero

By replacing manual issue verification with isolated AI subagents running in GitHub Actions, the Astro maintainers reduced open issue count by 85%. This post explores the architecture behind automated bug reproduction, patch verification,…

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