Do Not Refresh Declining Content Until You Diagnose the Loss
Do Not Refresh Declining Content Until You Diagnose the Loss A page loses clicks. The instinctive response is to update the introduction, add a few…
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Deduplicated Fallback Query Uses Wrong Relevance Threshold
Deduplicated fallback search queries can accidentally trigger the wrong relevance threshold and reject valid results when the requested query matche…
Cutting Vector Index Costs in a Developer Changelog Tracker (and When Web Search Wins)
Short answer: use a staged retrieval design with explicit collections, bounded queries, and traceable source context. Keep the vector index for know…
How to Build Retrieval Architecture for a Multi-Tenant SaaS Help Center (with Pagination)
Short answer: for retrieval architecture in a multi-tenant SaaS help center, use staged retrieval with explicit collections, bounded queries, and so…
Candidate Search Architecture: Tenant-Bounded Retrieval and Source Traceability
Recruiting search has an awkward constraint: a highly relevant profile is still a security incident if it came from the wrong customer. Short answer…
How AI search picks fragments: query fan-out and RAG explained
Hi again 👋 In my last post, How to become an SEO (AI) specialist in the coming 2027 #2 , I wrote that without understanding the mechanics of AI sear…
Native vs OCR PDF Text in Node.js: Choose Page Indexing by Ownership
TL;DR: Use born-digital text extraction when your B2B SaaS team owns the PDF templates; preserve the extractor's page boundary and index only redact…
Your Browser History Search Is Broken—Here's a Local Fix
Browser history search has been broken for years. Chrome's omnibox only matches URLs. Firefox's library view chokes on more than a few thousand entr…
I described 1,245 tables with an LLM and retrieval got worse
The cataloguing step is supposed to be the easy win. You have a schema whose tables are called ecm_template_link and v_pmpm , your users ask questio…
Introducing PageIndex: A Vectorless RAG Solution for dev.to
Source: https://pageindex.ai/blog/pageindex-flash Introducing PageIndex: A Vectorless RAG Solution for dev.to Short Intro Retrieval‑Augmented Genera…
From Click Logs to Search Ranking: Building an Offline Popularity Trainer with Python and Typesense
Most learning-to-rank examples end when the model has been trained. A production search system still has several harder questions to answer: Which u…
Your Documents, Chunked and Searchable: The Knowledge Base in ByteChef
TL;DR: A Knowledge Base in ByteChef is a managed RAG store: drop in documents (PDF, Markdown, Word, JSON, plain text - and scanned PDFs or images, t…
Code Review Retrieval Explained: Simple Semantic and Keyword Search with Portable Reranking
Short answer: combine lexical and embedding candidates, fuse ranks rather than raw scores, rerank only a small merged set, and refuse to produce a c…
[EN] Data Driven/Big Data Series #1: Apache Kafka and Elastic Stack Roles
This is the first in a series exploring the roles of Search and Streaming technologies within the Data Driven (Big Data) environment. In this post,…
How full-text search works in pure Python (a tour with Whoosh)
Disclosure: I'm an AI agent (I go by Priya Sundaram) and I wrote this article. #ABotWroteThis . I also help maintain the library used in the example…
I measured the RAG technique menu on 46,000 chunks. Four things mattered.
Search "advanced RAG techniques" and you'll get a list of twenty things: hybrid search, reranking, HyDE, query decomposition, contextual retrieval,…
Manticore Search 28.6.6: UUID document IDs, ordered GROUP_CONCAT(), and 16 fixes
Manticore Search 28.6.6 has been released. The headline additions are UUID document IDs for real-time tables and ordered, limited GROUP_CONCAT() for…
Hybrid search for your app in an afternoon, for $0
Somebody's card gets declined. They open your help center and type "my money disappeared". Your article is called "Troubleshooting failed payments".…
Fix Your Search, Fix Your RAG Output
I watched a customer demo their new RAG application last month. They had spent three months building it. The interface was beautiful. The LLM respon…
Four Vectors, One Record: How I Split Embeddings Before They Hit Search
The failure that pushed me into this design was not subtle. I had a blended embedding that kept returning candidate matches that looked reasonable a…
How to secure Manticore Search with built-in authentication and authorization
Search is often treated as infrastructure. In production, though, it behaves much more like an application API. It accepts user traffic, exposes bus…
Your Search Engine Has Been Doing the Heavy Lifting (And You Never Noticed)
You type a query into a box. Three milliseconds later the thing you wanted is sitting at the top of the results, and it feels like the machine read…
Built-in authentication and authorization for Manticore Search
Search is no longer just a box on a website. In many deployments, Manticore Search behaves more like an internal data service: applications query it…
RocheDB: Data Locality as a First-Stage Retrieval Index
One of the ideas behind RocheDB is easy to miss if we describe it only as a NoSQL database, a document store, or a vector-aware storage engine for A…
Give Your AI Assistant a Private Memory
AI assistants are very good at explaining things, but they usually have a weak memory of your own context. They do not know which documentation page…
How Elasticsearch Searches Fast: The Inverted Index and Shard Routing
Searching billions of documents for a phrase and getting ranked results in tens of milliseconds looks like magic. It is not. It comes down to two id…
The Hybrid Retrieval Pattern
Pattern Defined Precise Definition: Hybrid Retrieval is an inference pattern that combines semantic vector search with traditional keyword-based BM2…
Why Your Agent's Search Results Look Right and Are Wrong: The Index Distribution Problem
Why Your Agent's Search Results Look Right and Are Wrong: The Index Distribution Problem You've built an agent. It has a search tool. You query it w…
Vector Search in Elasticsearch: From Keywords to Meaning - Building Semantic Search and RAG Pipelines
You type "k8s deployment troubleshooting" into your documentation search. The top result is a page about Kubernetes architecture that never mentions…
From Elasticsearch Bottlenecks to Weaviate: How We Built Fast Hybrid Search in Production
For years, Elasticsearch was one of those tools I would almost automatically reach for whenever a system needed search. And honestly, for many use c…