2d ago · 6 min read · Every RAG tutorial shows you fixed-size chunking in five lines of code. Nobody shows you what happens six months later when your retrieval quality has collapsed and you can't figure out why. This arti
Join discussionApr 13 · 11 min read · The single most common mistake I see in RAG projects is this: a team spends a month tuning their embedding model and another month picking a vector store, and their retrieval quality is still mediocre. They conclude "RAG is hard." They start looking ...
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Jan 26 · 2 min read · Most Retrieval-Augmented Generation systems do not fail loudly. They decay. Accuracy slowly drops. Answers become vague. Users lose trust. Teams often blame the LLM. In reality, the failure usually lives in the vector layer. Three silent killers domi...
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Nov 28, 2025 · 10 min read · Se você está começando a se aventurar no mundo de AI Engineering e quer ir além do básico, precisa entender profundamente o que é Retrieval-Augmented Generation (RAG). Essa técnica é, sem dúvida, um divisor de águas para quem quer construir agentes d...
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Nov 4, 2025 · 7 min read · TL;DR:Retrieval-Augmented Generation (RAG) helps large language models (LLMs) like GPT-5 and Claude 4.5 access private, real-time, or domain-specific data by retrieving relevant chunks before generating answers. This article breaks down what RAG is, ...
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Oct 28, 2025 · 6 min read · Introduction In specialized fields, smarter systems are the goal. While scaling large language models (LLMs) is popular, real improvements often come from optimizing the backend. Retrieval-Augmented Generation (RAG) pipelines, particularly chunking, ...
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Oct 21, 2025 · 8 min read · Introduction In today's data-driven world, organisations are drowning in documents while struggling to extract meaningful insights from them. Traditional search methods fall short when dealing with complex, unstructured content that requires contextu...
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Oct 8, 2025 · 4 min read · Imagine having an AI that actually knows your internal data and can answer questions instantly. In this guide, I’ll walk you through building an internal knowledge assistant using LLMs and vector search, showing how embeddings and retrieval-augmented...
Join discussionAug 22, 2025 · 6 min read · Common Failure Cases and Quick Mitigations Retrieval-Augmented Generation (RAG) has revolutionized how Large Language Models (LLMs) access and utilize external knowledge, enabling them to generate more accurate, relevant, and up-to-date responses. Ho...
Join discussionAug 20, 2025 · 4 min read · Generative AI models like ChatGPT are powerful, but they have one big limitation: they only know what they were trained on. If you ask about very recent events, your company’s private data, or a niche topic, they may “hallucinate” and give wrong or i...
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