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Endigest AI Core Summary
This article explains how Spotify built the Wrapped Archive feature, generating 1.4 billion personalized LLM-based listening reports for approximately 350 million users.
•A priority-ordered set of heuristics identified up to five remarkable days per user, including Biggest Discovery Day, Most Nostalgic Day, and Most Unusual Listening Day
•Prompts were split into a system prompt (tone, safety rules, data-driven storytelling contract) and a user prompt (listening logs, stats block, prior reports, user country)
•A distillation pipeline fine-tuned a smaller production model on curated frontier-model outputs, then applied Direct Preference Optimization (DPO) using A/B-tested human evaluations
•A column-oriented key-value database used date-based column qualifiers (YYYYMMDD) per remarkable day to enable concurrent writes without locks or read-modify-write races
•Infrastructure was pre-scaled hours before launch and synthetic load tests were run to warm caches; LLM-as-a-judge evaluated ~
This summary was automatically generated by AI based on the original article and may not be fully accurate.
Spotify
Google Cloud
Databricks
Stripe