Vector-Search

Diagram of a hybrid retriever with sparse and dense branches feeding a reranker.

Build a Hybrid Sparse-Dense Retriever: A CV-Worthy RAG Side Project

Hands-on build guide for a hybrid sparse-dense retriever (BM25 + embedding reranking) with a from-scratch HNSW vector index. Real runnable code, architecture diagrams, and a roadmap to senior-level.

Diagram showing sparse and dense retrieval paths merging into a fused ranked list feeding a streaming generation loop.

Build a Hybrid Sparse-Dense Retriever from Scratch: A CV Project That Actually Signals Systems Skill

Step-by-step build of a real hybrid retrieval system that combines learned BM25 with dense embeddings, fuses scores, and streams answers — the kind of project that makes hiring managers stop scrolling.

Architecting Retrieval-Augmented Generation Systems: A Deep Dive into Production Pipelines

How to design Retrieval-Augmented Generation pipelines that hold up in production — covering indexing, hybrid retrieval, reranking, evaluation harnesses, and the operational realities of freshness, latency, and cost.

Diagram-style illustration contrasting retrieval and cache flows feeding into an LLM.

RAG vs CAG: What the Difference Actually Means in Production

A practical, architecture-first comparison of Retrieval-Augmented Generation and Cache-Augmented Generation, with patterns for combining both in production LLM systems.

Architecting Low-Latency Cross-Regional Replication for Vector Search Clusters: Design Patterns and Implementation Strategy

A deep dive into the architecture, patterns, and concrete steps needed to achieve sub‑10 ms cross‑regional vector search replication at scale.