Designs

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All designs 7

Ordered by design number

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RetrievalClear filters

Practice briefStart with your own approach
18. Keep enterprise AI search fresh and private
Handle document changes, ACL revocation and deletion across a retrieval pipeline.
AI systemsHard
Search Security Privacy
+3
AI systems Permissions Retrieval
Discuss
Practice
83. Design a Vector Database
Nearest-neighbour search over a billion embeddings: HNSW, IVF-PQ and disk graphs, filters, segments, sharding, and hybrid search with re-ranking.
ClassicMedium
Generative AI Search AWS
+6
Embeddings HNSW Hybrid search RAG Retrieval Vector search
Worked design
Practice
109. Design an Embedding Generation and Indexing Pipeline
Embed a billion chunks on GPUs, keep a k-NN index fresh through CDC with versioned writes and provable deletes, and migrate models blue-green.
ClassicMedium
Search AI infrastructure AWS
+4
Batch inference Embeddings Retrieval Vector search
Worked design
Practice
125. Design a Prompt and Semantic Cache for LLMs
Exact, semantic and prefix caching in front of LLMs: scoped keys, distances with an error budget, tenant isolation, invalidation and measured savings.
ClassicMedium
Caching Generative AI AI infrastructure
+4
AWS Embeddings LLMs Retrieval
Worked design
Practice
130. Design a Visual Search System
Search by photo over a billion images: contrastive embeddings from engagement pairs, object crops, IVF-PQ with re-scoring, versioned indexes.
ClassicMedium
Machine learning AWS Computer vision
+3
Embeddings Retrieval Visual search
Worked design
Practice
131. Design Retrieval-Augmented Generation
Answers from private documents with citations: chunking, BM25 + vector retrieval, reranking, permission filters, grounding checks and evaluation.
ClassicMedium
Generative AI AWS LLMs
+2
RAG Retrieval
Worked design
Practice
139. Design Similar Listings for a Vacation Rental Platform
Pick 12 homes a guest could book instead, from listing embeddings learned on browsing sessions, filtered by dates and party size, then ranked.
ClassicMedium
Machine learning AWS Embeddings
+3
Marketplace Recommendations Retrieval
Worked design
Practice

Each design brings together the brief, practice, examples and discussion.

All designs 7

18. Keep enterprise AI search fresh and private

83. Design a Vector Database

109. Design an Embedding Generation and Indexing Pipeline

125. Design a Prompt and Semantic Cache for LLMs

130. Design a Visual Search System

131. Design Retrieval-Augmented Generation

139. Design Similar Listings for a Vacation Rental Platform