#Systems Design

Articles about Systems Design — exploring patterns, best practices, and real-world implementations in production systems.

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Pratik Dhanave · ·6 min read

The Two-Stage Architecture

You cannot run your best, most expensive model on millions of items for every request — the latency and cost are impossible. The elegant, near-universal answer is to split recommendation into two stages: a cheap, fast net that narrows millions of items to a few hundred, followed by a precise, heavier model that ranks those few. This retrieve-then-rank structure is the single most important architectural pattern in production recommenders.

You can't run your best, most expensive model on millions of items per request. The near-universal answer is to split recommendation into two stages: a cheap, fast net that narrows millions to a few hundred, then a precise, heavier model that ranks those few. This retrieve-then-rank structure is the single most important architectural pattern in production recommenders — with an interactive pipeline diagram.

#Recommender Systems#AI Architecture#Machine Learning#Systems Design#Personalization

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.