Adding a Trust Boundary to a LlamaIndex RAG Pipeline
Your LlamaIndex app does not only retrieve documents. It decides which external text is allowed to become model context. That is a trust decision, eve…
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RAG vs MCP is the wrong debate — here's the right framing for production AI systems
The question I keep seeing in every AI engineering forum right now: "Should we use RAG or MCP?" It's the wrong question. And the fact that it's being …
Introducing Citai: the RAG engine I built across 6 articles — now free to try
Over the last 6 articles I shared how I built every piece of a production RAG engine: hybrid search, cross-encoder reranking, SSE streaming, multi-ten…
Day 1: Your Team’s Chat Is a Wiki Waiting to Happen — A New Kind of RAG
Why we built Beever Atlas — and why “distill first, retrieve second” works where vanilla RAG falls apart. By Alan Yang Your team already documents eve…
A Unified View of AI Evolution: From Machine Learning to LLMs, RAG, and Fine-Tuning
Artificial Intelligence has progressed far beyond its early rule-based origins. What once depended on predefined logic has evolved into systems that c…
Cloudflare Boosts AI Agent Governance; Claude Model Choice & Advanced NLP
Cloudflare Boosts AI Agent Governance; Claude Model Choice & Advanced NLP Today's Highlights This week's highlights include Cloudflare's new enter…
Your RAG Eval Set Is Probably Wrong. The Test That Catches It.
Book: RAG Pocket Guide Also by me: LLM Observability Pocket Guide My project: Hermes IDE | GitHub — an IDE for developers who ship with Claude Code an…
Postgres With pgvector vs Pinecone: 1 Million Embeddings, One Honest Comparison
Book: Database Playbook: Choosing the Right Store for Every System You Build Also by me: RAG Pocket Guide: Retrieval, Chunking, and Reranking Patterns…
5 RAG Failure Modes Nobody Warns You About in the Tutorials
Book: RAG Pocket Guide: Retrieval, Chunking, and Reranking Patterns for Production Also by me: Database Playbook: Choosing the Right Store for Every S…
Наглядный пример, зачем нужны агенты
Расскажу историю длиною в полгода, на которой прекрасно прочувствовал все прелести современных инструментов и способов эксплуатации llm. Идея до жути …
Part 4: Improving Retrieval Quality with Token-Aware Chunking and HyDE
Making RAG Smarter with Token-Aware Chunking, HyDE, and Context-Aware Search In Part 3, we improved chunking and optimized context. The system was fas…
Introduction to RAG for LLMs: Sparse (Lexical) RAG and Dense RAG (Semantic Vector Search)
Introduction LLMs store information within their own parameters. By being trained on massive datasets, the models learn this data. But what if they ar…
Plexus: A WiFi Graph RAG for Network Troubleshooting
WiFi troubleshooting has a confidence problem. Ask a chatbot what's causing client disconnections and it'll give you an answer that sounds right. But …
5 Ways Azure AI Search is Revolutionizing Enterprise RAG Architectures
In the rapidly evolving landscape of Generative AI, the transition from experimental Proof of Concepts (POCs) to production-grade applications is the …
Stop Losing Your Health Data! Build a Lifelong Electronic Health Record (EHR) System with Neo4j and GraphRAG 🏥💻
Let’s be honest: our medical history is usually a chaotic mess of scattered PDFs, blurry smartphone photos of prescriptions, and "I think I had a feve…
785 статей. 26 доменов. Для агентов, не людей
Когда AI-агент пишет код в пустом проекте, первые 30-40% токенов он тратит на ориентацию — читает README, туториалы, API-reference. Ни один формат не …
Как получать эффект от ИИ, когда нет железа
Вы уверены, что для внедрения корпоративного ИИ в закрытом контуре нужны суперкомпьютеры? Мы решили это проверить и добиться вменяемого качества от кр…
Migrating vector embeddings in production without downtime
In the fast-moving world of AI, models evolve rapidly. What was state-of-the-art six months ago is now being surpassed by newer models. For a RAG syst…
Scrape vs Crawl vs Map: Picking the Right Anakin API for the Job
Scrape vs Crawl vs Map: Picking the Right Anakin API for the Job You have a website you need data from. You open the docs, see three APIs that all sou…
FLAMEHAVEN FileSearch: Why This RAG Engine Feels Different from the Usual Stack
FLAMEHAVEN FileSearch: Why This RAG Engine Feels Different from the Usual Stack RAG is no longer an exotic idea. At this point, most developers have s…
Собираем AI-агента нового поколения: Python, RAG и внешние инструменты через MCP (Model Context Protocol)
Ещё пару лет назад типичное LLM-приложение выглядело как последовательная цепочка вызовов: взяли промпт, добавили контекст из векторной базы, отправил…
The Hidden Compliance Gap in Every Enterprise RAG Pipeline
Every week, another enterprise announces a RAG-powered AI assistant. Legal teams get a contract review bot. Hospitals get a clinical decision support …
Two Weeks of My News Aggregator: RAG Chat and a Sentiment Dial
Originally published on my blog Two weeks ago I shipped my news aggregator as a finished Symfony 8 app — fetch feeds, enrich with AI, send alerts, gen…
RAG in Practice — Part 5: Build a RAG System in Practice
Part 5 of 8 — RAG Article Series ← Part 4: Chunking, Retrieval, and the Decisions That Break RAG · Part 6 (publishing soon) Why This Article Is Differ…
What is RAG? A Beginner's Guide to Retrieval-Augmented Generation (With a Full Pipeline Walkthrough)
If you've ever wondered how ChatGPT-style apps can suddenly "know" about your company's internal documents, product manuals, or legal files without be…
Почему ваш AI-агент тратит 80% токенов на файлы, которые уже читал вчера — и как это починить тремя markdown-файлами
В прошлой статье я разобрал почему Claude Code ломает проекты (context drift, отсутствие CLAUDE.md , нет хуков на тесты) и как выстроить защиту от рег…
Why I built ragwise: pip-installable RAG with hybrid search, streaming, and agent tools by default
I spent a weekend integrating a RAG pipeline into a client project using LangChain. By Sunday evening I had 200 lines of boilerplate, a requirements.t…
Building an AI-Powered Detection System with Hindsight Memory Integration
Introduction Modern AI systems are becoming increasingly powerful in detecting scams, deepfakes, and suspicious patterns. However, one major limitatio…
Offline Evaluation of RAG-Grounded Answers in LaunchDarkly AI Configs
Overview This tutorial shows you how to run an offline LLM evaluation on the RAG-grounded support agent you built in the Agent Graphs tutorial , using…
LLM vs RAG
LLM (Large Language Model) An LLM like GPT-4 or Claude is: A pretrained model on massive text data Generates answers based on what it has learned duri…