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    <title>RAG on Manvendra Rajpoot</title>
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      <title>AI/LLM Cheatsheet 05 — RAG Patterns</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/05-rag-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 06:40:00 +0530</pubDate>
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      <description>RAG — retrieve &#43; generate, hybrid, rerank, citations.</description>
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      <title>Evaluating RAG Systems in 2026 — Retrieval Quality, Faithfulness, and the Metrics That Matter</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-rag-evaluation-2026/</link>
      <pubDate>Sat, 02 May 2026 09:20:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-rag-evaluation-2026/</guid>
      <description>RAG evaluation in 2026 — retrieval metrics (recall, MRR), generation metrics (faithfulness, relevance), Ragas, and the patterns from production RAG.</description>
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      <title>Hybrid Search with Postgres in 2026 — pgvector &#43; FTS &#43; Reranker</title>
      <link>https://blog.rajpoot.dev/posts/postgresql/postgres-pgvector-hybrid-search-2026/</link>
      <pubDate>Fri, 01 May 2026 04:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/postgresql/postgres-pgvector-hybrid-search-2026/</guid>
      <description>How to build hybrid search in Postgres in 2026 — combining pgvector and full-text search with RRF fusion, plus a reranker, for production RAG.</description>
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      <title>Giving AI Agents Memory in 2026 — Mem0, Zep, and the Patterns That Work</title>
      <link>https://blog.rajpoot.dev/posts/ai/agents-with-memory-mem0-zep-2026/</link>
      <pubDate>Thu, 30 Apr 2026 13:40:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/agents-with-memory-mem0-zep-2026/</guid>
      <description>How to give AI agents long-term memory in 2026 — Mem0, Zep, hand-rolled memory layers, summary memory, and the architecture that scales.</description>
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      <title>1M-Token Context Windows in 2026 — When They Help, When They Hurt</title>
      <link>https://blog.rajpoot.dev/posts/ai/long-context-1m-tokens-2026/</link>
      <pubDate>Thu, 30 Apr 2026 13:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/long-context-1m-tokens-2026/</guid>
      <description>Practical guide to 1M-token context windows in 2026 — when long context replaces RAG, when it doesn&amp;#39;t, prompt caching, and the cost reality.</description>
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      <title>Agentic RAG in 2026 — When Retrieval Becomes a Tool, Not a Pipeline</title>
      <link>https://blog.rajpoot.dev/posts/ai/agentic-rag-2026/</link>
      <pubDate>Thu, 30 Apr 2026 13:00:00 +0530</pubDate>
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      <description>Agentic RAG explained — when the agent decides what and when to retrieve, multi-step reasoning, query rewriting, self-reflection, and the patterns that beat naive RAG.</description>
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      <title>Rerankers in RAG — The Underrated Quality Multiplier in 2026</title>
      <link>https://blog.rajpoot.dev/posts/ai/rerankers-rag-quality-2026/</link>
      <pubDate>Thu, 30 Apr 2026 12:30:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/rerankers-rag-quality-2026/</guid>
      <description>Why rerankers are the highest-ROI upgrade to a RAG system in 2026 — Cohere Rerank, BGE-Reranker, JinaAI, cross-encoders, and how to wire one into a production pipeline.</description>
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      <title>Embedding Models in 2026 — OpenAI, Voyage, Cohere, BGE, and How to Pick</title>
      <link>https://blog.rajpoot.dev/posts/ai/embeddings-models-comparison-2026/</link>
      <pubDate>Thu, 30 Apr 2026 12:20:00 +0530</pubDate>
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      <description>How to pick an embedding model in 2026 — OpenAI text-embedding-3, Voyage, Cohere, BGE, and the open-source landscape. Quality, cost, dimensions, multilingual support.</description>
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      <title>Fine-Tuning vs RAG vs Prompting in 2026 — How to Pick the Right Approach</title>
      <link>https://blog.rajpoot.dev/posts/ai/fine-tuning-vs-rag-vs-prompting-2026/</link>
      <pubDate>Wed, 29 Apr 2026 10:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/fine-tuning-vs-rag-vs-prompting-2026/</guid>
      <description>When to fine-tune, when to RAG, and when to just prompt — a practical 2026 decision guide for LLM applications, with cost, quality, and ops tradeoffs.</description>
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      <title>Build a Production RAG App with pgvector and FastAPI in 2026</title>
      <link>https://blog.rajpoot.dev/posts/ai/build-rag-app-pgvector-fastapi/</link>
      <pubDate>Tue, 28 Apr 2026 16:00:00 +0530</pubDate>
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      <description>A complete, copy-paste guide to building a Retrieval-Augmented Generation (RAG) backend with PostgreSQL &#43; pgvector and FastAPI — chunking, embeddings, hybrid search, and the parts most tutorials skip.</description>
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