Build AI that recommends products, articles, or content based on user preferences. Use when building product recommendations, you-might-also-like features, personalizing feeds, content discovery, ranking by user preference, suggesting related items, building a recommendation engine, collaborative filtering with LLMs, re-ranking search results by relevance, curating personalized playlists, next-bes
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ai-recommending
Build an AI recommendation engine using DSPy. The core pattern is two-stage - embedding-based retrieval to get candidate items, then an LM re-ranker that personalizes the ranking using user profile signals and generates human-readable explanations.
Step 1 - Understand the recommendation task
Before writing code, clarify:
What items are you recommending? Products, articles, support docs, videos, playlists?
What signals do you have? Purchase history, click hist
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