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DODUSHYANTH O Ahowragworksunderthehoodbanner.hashnode.dev4d ago · 7 min read

Demystifying Retrieval-Augmented Generation: An Engineering Deep-Dive into Document Processing, Vector Search, and Context Construction

1. Introduction & The Hallucination Problem Imagine deploying a state-of-the-art Large Language Model (LLM) to assist engineers with your company’s 500-page internal infrastructure specification or a

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Iiniyarajaniniyarajanhashnodedev.hashnode.devMay 8 · 7 min read

Vector Database Tutorial: Building Smart AI Agents with RAG

Photo by Brett Sayles on Pexels You're staring at your AI agent's lackluster responses, wondering why it keeps hallucinating facts about your company's products. The truth is, most developers jump straight into building agents without understanding t...

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Iiniyarajaniniyarajanhashnodedev.hashnode.devApr 15 · 8 min read

Building Robust AI Agent Memory Systems in 2026

Picture this: you've built an AI agent that can handle customer support tickets brilliantly, but it keeps asking the same customer their name and order number in every conversation. Sound familiar? We've all been there — creating agents that work per...

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Iiniyarajaniniyarajanhashnodedev.hashnode.devApr 1 · 9 min read

Building Persistent AI Agent Memory Systems That Actually Work

Building Persistent AI Agent Memory Systems That Actually Work Photo by Andrey Matveev on Pexels Here's a startling fact: 87% of AI agents fail at multi-turn conversations because they can't remember context beyond their immediate training window. W...

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TITech Insights Hubtopperblog.hashnode.devFeb 16 · 11 min read