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Recent posts tagged rag

Description for Tag: "rag"

Retrieval-Augmented Generation, a method for integrating information retrieval into language model responses.
Level UI • 19 hours • in Articles • 9 min read
An MCP server is not a new API. It is a thin layer over the one you already have
Somewhere in the last year, "do we need an MCP server?" joined the list of questions that arrive in a brief before anyone has said what the thing is for. It is usually framed as MCP vs API, as though the Model Context Protocol were a newer kind of AP...
post-cover-33074
  • ai
  • api
  • webdev
  • security
7 Reactions 7 Comments
Aqib Javaid • Oct 22 • in Articles • 5 min read
Why Your RAG Chatbot Gives Wrong Answers (and How to Fix It)
You built a chatbot on your own documents, and it still answers with confident nonsense. Customers get wrong prices, invented policies or a polite "I don't know" when the answer is on your website. This is the most common complaint I hear about RAG c...
  • ai
  • rag
  • llm
  • chatbot
1 Reactions 1 Comments
uglypeardata • Oct 21 • in Articles • 14 min read
Legal Knowledge Bases on Premise: Compression, Tokens, and RAG Without Leaking Data
If you are an engineer asked to build "a searchable legal knowledge base" for a law firm or an in-house legal team, the easy part is the search UI. The hard part is everything underneath: hundreds of gigabytes of scanned contracts, stamped pages, e...
post-cover-32025
  • rag
  • knowledge-graphs
  • aiagents
2 Reactions 1 Comments
xcrawlapi • Oct 20 • in Articles • 2 min read
Building a Small RAG Index from Documentation Pages: Map First, Then Scrape
When you want an LLM to answer questions about a product's docs, the hard part is rarely the vector store. It is getting clean, current text out of the pages in the first place. Raw HTML is full of navigation, cookie banners and script tags that wast...
  • rag
  • llm
  • webscraping
  • python
2 Reactions 1 Comments
A.Talaat • Oct 16 • in Articles • 2 min read
Building RAG on PostgreSQL with Pgvector and Ruby on rails
🧠 Your Database Is Already a Vector Database Most RAG tutorials start the same way: "First, spin up a vector database." But Stop. If you're on Rails, you already have PostgreSQL. With the pgvector extension it can store and search embeddings and...
post-cover-31432
  • ruby
  • rails
  • rag
  • ai
5 Reactions 4 Comments
uglypeardata • Oct 16 • in Articles • 5 min read
Building a Private RAG Pipeline That Doesn't Leak Patient Data
!http:// If you have ever wired up a retrieval-augmented generation system for a normal company, the healthcare version will feel familiar and then suddenly will not. The retrieval math is the same. The constraints are a different sport. This is a w...
post-cover-31299
  • rag
  • ai
  • compression
0 Reactions 0 Comments
Tom Smithverified • 15 hours • in Articles • 9 min read
Developer Weekly Briefing — October 30, 2026
Security dominated this week, but not in the usual way. Two active campaigns turned GitHub configuration files into attack surfaces. Researchers demonstrated that the built-in browsers inside AI coding tools can read your SSH keys. And at Oracle AI ...
post-cover-33104
  • agenticai
  • devsecops
  • github
  • localai
6 Reactions 3 Comments
Sabi Mantock • Oct 12 • in Articles • 3 min read
Learning LangChain
A while back I built Synapse, a small app that answers questions using my own notes. I did every part of it by hand: load the files, turn them into vectors, find the closest ones to the question, and hand those to an LLM. It worked, and I understood ...
post-cover-30850
  • langchain
  • rag
  • ai
5 Reactions 3 Comments
Dharanidharan • Oct 8 • in Articles • 4 min read
Why Your RAG Chatbot Gives Wrong Answers (And How to Fix It)
You built a "chat with your documents" app. You upload a PDF, ask a simple question, and the answer is wrong, half right, or completely made up. If this happened to you, do not blame the AI model yet. In most RAG apps, wrong answers come from a few ...
post-cover-30306
  • chatbot
  • rag
  • webdev
  • programming
0 Reactions 4 Comments
Dharanidharan • Oct 7 • in Articles • 4 min read
How to Build a "Chat With Your PDFs" App: A Simple RAG Guide
Ever wanted to upload a PDF and just ask it questions instead of scrolling through fifty pages? That is what a "chat with your PDF" app does, and it works using a technique called RAG Retrieval-Augmented Generation. In this guide, I will explain wha...
post-cover-30154
  • webdev
  • aiagents
  • python
  • rag
0 Reactions 0 Comments
syedahmershah • Oct 6 • in Articles • 11 min read
RAG Retrieval Strategies on a 50k-Document Dataset: BM25 vs Dense vs Hybrid
> TL;DR > - On 50k documents, retrieval quality matters more than your choice of vector database. At this size you can run exact search and skip the infrastructure. > - BM25 is great at exact terms error codes, names, IDs and weak at paraphrases. Den...
post-cover-30044
  • syedahmershah
  • ai
  • ahmershahdev
  • rag
1 Reactions 1 Comments
JAgostoni • Oct 3 • in Articles • 9 min read
Is It Still RAG If There's No Retrieval?
I've been shipping software for 28 years, 21 of them as a consultant working across over 100 different engagements. Past a certain point, a resume stops being a record and becomes a burdensome editing problem. Two pages can barely hold a half-dozen e...
post-cover-29679
  • ai
  • rag
  • jobs
  • chatbot
9 Reactions 3 Comments
Myzubster • Sep 28 • in Articles • 10 min read
Engineering an Evidence-First Knowledge Graph: From GitHub Artifacts to On-Chain Proofs in MyZubster
Certo. Per CoderLegion lo farei più tecnico del post DEV, con più attenzione ad architettura, data provenance, canonicalizzazione, hashing e al motivo per cui dopo il test con Nicola stiamo valutando standard esistenti invece di continuare ad aggiung...
  • opensource
  • rag
  • web3
  • nodejs
2 Reactions 0 Comments
ManSio • Sep 27 • in Articles • 7 min read
Nine Days, 143 Commits: a Forensic History of the Unit-of-Return Experiment
Every SHA, every raw number and every recovered file below is traceable to the repo. Where something broke, the commit that fixed it is named. Where something is still open, it says so. Prologue: a Table in the Comments On September 24, a comment...
post-cover-28802
  • ai
  • rag
  • python
  • architecture
6 Reactions 2 Comments
Datalaria • Sep 25 • in Articles • 6 min read
GraphRAG: Why Vectors Aren't Enough and Your AI Needs a Knowledge Graph
You ask your traditional RAG pipeline an apparently straightforward enterprise question: > “Analyze all 500 contracts and technical audits from the past two years and tell me the three recurring operational bottlenecks shared by our tier-1 suppliers...
post-cover-28581
  • graphrag
  • knowledge
  • rag
  • vectors
2 Reactions 0 Comments
immanuel-gabriel • Sep 24 • in Articles • 2 min read
FreshContext: inspecting context before an agent uses it
The passage an agent retrieves can be relevant and still unsuitable for the job in front of it. An old document may be useful background. A recent-looking record may have no traceable source. A failed request should not become evidence just because i...
  • ai
  • rag
  • testing
5 Reactions 2 Comments
DaCverified • Sep 22 • in Articles • 4 min read
I Wanted a RAG System That Could Show Its Work, So I Built Alchimista
Most RAG demos stop at the answer.Alchimistahttps://github.com/Daniele-Cangi/Alchimista You upload a document, ask a question, get a plausible response, maybe see a few source chunks, and that's where the story ends. But I kept coming back to a dif...
post-cover-28173
  • showdev
  • ai
  • rag
  • security
4 Reactions 2 Comments
ManSio • Sep 22 • in Articles • 6 min read
From a Test-Suite Trace to a Search Signal: the Bootstrap Pipeline Story
Where It Started The problem to which everything traces back: RAG search across an unfamiliar codebase sees the code, but misses the intent. Embeddings find a chunk by keywords, PropertyGraph finds a symbol by name, but to the question "where is t...
post-cover-28140
  • search
  • rag
  • codearchitecture
  • testing
7 Reactions 0 Comments
René Zander • Sep 16 • in Tutorials • 1 min read
Knowledge Graph Evaluation: Scoring 12 Real Decisions
Three weeks ago I started scoring my knowledge graph against the answer I would have reached without it. It earns its place: 6 of 12 decisions came out sharper, 2 errors never reached real work, and 73 minutes of research time saved. The Metric That...
post-cover-27367
  • rag
  • knowledge-graphs
  • ai
  • aiagents
0 Reactions 1 Comments
Posted in Dev Stories group
James Dayalverified • Sep 9 • in Articles • 12 min read
25 Years in Tech Taught Me What AI Still Can't Replace — Helkyn Coello's Developer Journey
25 Years in Tech Taught Me What AI Still Can't Replace — Helkyn Coello's Developer Journey Technology has changed dramatically over the past 25 years. Desktop applications became client-server systems. Client-server systems became web platforms. A...
post-cover-26566
  • ai
  • rag
  • devjourney
3 Reactions 0 Comments
Basavaraj-Shepur • Sep 7 • in Articles • 2 min read
The KV Cache Formula That Should Set Your Context Limit
Phone prices are climbing this year largely because memory is scarce - AI data centers are buying DRAM faster than fabs can make it. That same squeeze shows up in your cloud bill, and it changes which knob you turn first when inference gets expensive...
post-cover-26423
  • rag
  • llm
  • gpu
  • agenticai
0 Reactions 0 Comments
helkyn-coello • Sep 2 • in Articles • 6 min read
Is Your Knowledge Base Actually Thinking, or Just Retrieving?
A while back I was able to build a working knowledge base in less than an hour. Fifty-five minutes to be accurate. I started by opening VS Code with Claude Code in the side panel. I had documentation scattered across roughly ten training manuals, a v...
post-cover-25823
  • rag
  • llm-applications
  • ai
  • enterpriseai
0 Reactions 0 Comments
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