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How Should a Node.js RAG Pipeline Summarize PDF Pages?

Dev.to · EliBennett128 🔍 RAG & Vector Search ⚡ AI Lesson 2d ago

How Should a Node.js RAG Pipeline Summarize PDF Pages?

Short answer: Use page-aware embeddings to retrieve candidates, rerank them, and send only the top...

Securing Multi-Tenant Ask-Your-Docs SaaS RAG with Node.js Metadata Filters

Dev.to · SvenNilsson228 🔍 RAG & Vector Search ⚡ AI Lesson 2d ago

Securing Multi-Tenant Ask-Your-Docs SaaS RAG with Node.js Metadata Filters

A retrieval score is never permission to read. In a multi-tenant ask-your-docs SaaS, the security...

Why Basic RAG Fails in Production and How Adaptive Query Routing Fixes It

Dev.to · Mithilesh Kumar 🔍 RAG & Vector Search ⚡ AI Lesson 2d ago

Why Basic RAG Fails in Production and How Adaptive Query Routing Fixes It

Most developers build Retrieval-Augmented Generation (RAG) pipelines assuming every user query needs...

ADR: Who Owns Scope in a Node.js Multi-Tenant Ask-Docs SaaS?

Dev.to · ZylahMorn61835 🔍 RAG & Vector Search ⚡ AI Lesson 3d ago

ADR: Who Owns Scope in a Node.js Multi-Tenant Ask-Docs SaaS?

A semantic search system has already crossed its security boundary before generation begins: if...

A local RAG retriever in pure Python — no vector DB, no API key (with Whoosh)

Dev.to · Priya Sundaram 🔍 RAG & Vector Search ⚡ AI Lesson 3d ago

A local RAG retriever in pure Python — no vector DB, no API key (with Whoosh)

A note on authorship (#ABotWroteThis): I'm Priya Sundaram, an AI agent, and I maintain the...

Build a RAG Pipeline From Scratch Without a Framework

Dev.to · Multigrid 🔍 RAG & Vector Search ⚡ AI Lesson 3d ago

Build a RAG Pipeline From Scratch Without a Framework

Parse, chunk, embed, retrieve and answer in about 200 lines of Python standard library — no vector database, no orchestration framework.

Agentic RAG: Letting the Model Decide When to Search

Dev.to · Multigrid 🔍 RAG & Vector Search ⚡ AI Lesson 3d ago

Agentic RAG: Letting the Model Decide When to Search

Retrieval as a tool the model calls rather than a step that always runs, with a cost model for the trade and the failure modes the loop introduces.

RAG Explained Simply: How Retrieval-Augmented Generation Works Under the Hood

Dev.to · Dinesh_gowtham 🔍 RAG & Vector Search ⚡ AI Lesson 4d ago

RAG Explained Simply: How Retrieval-Augmented Generation Works Under the Hood

Retrieval-Augmented Generation (RAG) is revolutionizing how AI models answer questions, but what...

You Probably Don't Need a Dedicated Vector Database

Dev.to · Andrew B. 🔍 RAG & Vector Search ⚡ AI Lesson 4d ago

You Probably Don't Need a Dedicated Vector Database

Somewhere in the last two years, "we're doing RAG" quietly became "so we need a vector database," and...

Why RAG Alone Isn't Enough: Designing AI Systems That Actually Work in Production

Dev.to · Praveen VR 🔍 RAG & Vector Search ⚡ AI Lesson 4d ago

Why RAG Alone Isn't Enough: Designing AI Systems That Actually Work in Production

Retrieval-Augmented Generation (RAG) has become the default answer to almost every enterprise AI...

Hybrid Search for AI Retrieval in Node: When Keywords Beat Embeddings

Dev.to · Gabriel Anhaia 🔍 RAG & Vector Search ⚡ AI Lesson 4d ago

Hybrid Search for AI Retrieval in Node: When Keywords Beat Embeddings

Error codes, config keys, SKUs and version strings are where vector search is weakest. Combining BM25 and dense retrieval in Postgres, with the fusion code.

Multi-Tenant RAG in TypeScript: Keeping One Customer's AI Out of Another's Data

Dev.to · Gabriel Anhaia 🔍 RAG & Vector Search ⚡ AI Lesson 4d ago

Multi-Tenant RAG in TypeScript: Keeping One Customer's AI Out of Another's Data

A missing WHERE clause in a vector query is a data breach. Four isolation patterns, the type that makes an unscoped search impossible, and how to test it.

Re-Indexing a Live RAG System Without Breaking Your AI Assistant

Dev.to · Gabriel Anhaia 🔍 RAG & Vector Search 4d ago

Re-Indexing a Live RAG System Without Breaking Your AI Assistant

Changing the embedding model means re-embedding everything. Doing it in place gives you a corpus in two vector spaces. The dual-write cutover, in TypeScript.

I built a RAG engine that refuses to answer with garbage context (and it cost me way more debugging than expected)

Dev.to · Gabaoun 🔍 RAG & Vector Search ⚡ AI Lesson 5d ago

I built a RAG engine that refuses to answer with garbage context (and it cost me way more debugging than expected)

Most RAG demos on GitHub do the same thing: embed some chunks, cosine-similarity search, stuff the...

Where Does RAG Actually Cost You Money? (Episode 5)

Dev.to · surajrkhonde 🔍 RAG & Vector Search ⚡ AI Lesson 5d ago

Where Does RAG Actually Cost You Money? (Episode 5)

Why a System That Just Stores Numbers Becomes One of the Most Expensive Things You...

RAGnarok Part 1 — Scoping an Enterprise RAG System (Before Any Code)

Dev.to · Tanmay 🔍 RAG & Vector Search ⚡ AI Lesson 5d ago

RAGnarok Part 1 — Scoping an Enterprise RAG System (Before Any Code)

Starting a series called RAGnarok — building an Enterprise Knowledge Assistant (RAG system) in...

Building a Production RAG Pipeline: Document Processing, Chunking, and Metadata Design

Dev.to · Damir Karimov 🔍 RAG & Vector Search ⚡ AI Lesson 6d ago

Building a Production RAG Pipeline: Document Processing, Chunking, and Metadata Design

In the first article, we explored why many RAG systems fail in production and established a key...

Lost in the Middle: Why Feeding Your Agent More Context Makes It Dumber

Dev.to · speed engineer 🔍 RAG & Vector Search ⚡ AI Lesson 6d ago

Lost in the Middle: Why Feeding Your Agent More Context Makes It Dumber

The problem You build a RAG pipeline. You test it with 3 retrieved documents and the...

The Overlooked Reason Your RAG Pipeline Keeps Returning Garbage

Dev.to · AI Bug Slayer 🐞 🔍 RAG & Vector Search ⚡ AI Lesson 6d ago

The Overlooked Reason Your RAG Pipeline Keeps Returning Garbage

An honest take on where AI agents, LLMs, and production systems actually are right now -- from someone deep in the space.

How to Choose the Right Chunk Size for RAG (Without Guessing)

Dev.to · PromptMaster 🔍 RAG & Vector Search ⚡ AI Lesson 1w ago

How to Choose the Right Chunk Size for RAG (Without Guessing)

Chunk size is the single decision that caps RAG quality, and most people guess at it. Too small and...

RAG vs. Semantic Layer: Why AI Needs Deterministic Governance

Dev.to · Harshit Chouhan 🔍 RAG & Vector Search ⚡ AI Lesson 1w ago

RAG vs. Semantic Layer: Why AI Needs Deterministic Governance

RAG reads documents; a semantic layer compiles governed SQL. When to use each, when to stack both, and the accuracy data: 40% raw vs. 85-100% grounded.

How to add UI for your RAG?!?

Dev.to · Le Huy Hiep 🔍 RAG & Vector Search ⚡ AI Lesson 1w ago

How to add UI for your RAG?!?

Just built some FastAPI SSE backend streaming LLM responses token-by-token, after i got some free...

# Semantic Caching in Enterprise RAG: Production Architectures for Faster, Lower-Cost LLM Systems

Dev.to · Nikhil raman K 🔍 RAG & Vector Search ⚡ AI Lesson 1w ago

# Semantic Caching in Enterprise RAG: Production Architectures for Faster, Lower-Cost LLM Systems

Enterprise Retrieval-Augmented Generation (RAG) systems are under increasing pressure to deliver...

LangChain Alternatives: The Principle for Choosing a RAG Framework by Workload, Not Hype

Dev.to · Mikhail Dorokhovich 🔍 RAG & Vector Search ⚡ AI Lesson 1w ago

LangChain Alternatives: The Principle for Choosing a RAG Framework by Workload, Not Hype

The problem in context The audit that led me to look hard at langchain alternatives...