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…
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Finding the Bugs I Built an AI Agent to Prevent: Building Deterministic Guardrails with LangGraph & Python
`` A real debugging log: fabrication bugs, deployment gaps, and false test passes found and closed across 6 rounds of adversarial testing. System pr…
Counting OpenAI Tokens per Request in FastAPI — Without Touching My Use Cases
I'm rebuilding evorag , a Python retrieval service: it chunks documents, embeds them with OpenAI's text-embedding-3-small , stores vectors in Postgr…
Building a RAG assistant that says “I don’t know”: evaluation, security and a $0 deployment
Most RAG tutorials end when the chatbot answers a question about a PDF. I wanted to find out what comes after that: how do you know it works, who is…
BOOTH Was Featured in Python Weekly: A Small Milestone for My Open-Source Project
A small milestone for a project I've been building: BOOTH was featured in Python Weekly! It appears in Python Weekly Issue #767 (October 15, 2026) u…
Travel Planner Retrieval Design with Bounded Access Rules and Source Citations
Short answer: a travel itinerary planner needs a staged retrieval architecture with bounded access rules and source context attached to every answer…
Claims Evidence Retrieval: Immutable Revisions for Insurance Intake Pipelines
Short answer: keep every uploaded claim document immutable, assign a monotonically increasing revision, and let retrieval filter by an explicit as-o…
Recruiting Candidate Search Source Deduplication — A 3-Stage Node.js Retrieval Design
Short answer: use a staged retrieval design with explicit collections, bounded queries, and traceable source context for recruiting candidate search…
Evaluating AI-Powered RAG Systems: Beyond Just Correct Answers
Artificial Intelligence is changing how we search for information and interact with documents. Retrieval-Augmented Generation (RAG) is an important…
Первый RAG комом: как мы учились анализировать ошибки автотестов с помощью LLM
Привет! Меня зовут Алексей, я автотестер в hh.ru . У нас около 3000 запускаемых классов с e2e (UI) тестами на Java. Они прогоняются по несколько раз…
Я добавил Rerank в Obsidian. Что показали тесты на 64 и 500 заметках
Добавил Rerank в свой плагин для Obsidian и решил проверить, стоит ли запускать вторую модель при каждом поиске. Сравнил три модели, провёл эксперим…
Как сделать RAG-чат для сайта, который не выдумывает цены: пять решений из моего бота
С июня я делаю AI-чат для сайтов, который не выдумывает цены и не соглашается с клиентом во всём подряд. К пяти решениям из статьи я пришёл через ош…
RAG Evaluation & Monitoring: Metrics, Frameworks & Production Observability
RAG Evaluation & Monitoring: Metrics, Frameworks & Production Observability Comprehensive guide to evaluating and monitoring Retrieval-Augme…
Building RAG from Scratch: No Frameworks Needed
Building RAG from Scratch: No Frameworks Needed Understand Retrieval-Augmented Generation by building it yourself — pure Python, zero dependencies.…
Insurance Claims Retrieval Architecture with Node.js: Five Access-Rule Checks
Short answer: use a staged retrieval design with explicit collections, bounded queries, and traceable source context; make access rules part of retr…
Building Better RAG
Most RAG systems that disappoint in production fail at retrieval, not generation: the model answers well from the wrong context, or from none at all…
The Atomic Answer Rule: Engineering Content for RAG Chunking and AI Search
The Atomic Answer Rule states that every H2 section of a document must answer its query as an independent, self-contained micro-document, without re…
Я написал 61 тест для AI-ментора. Потом выяснилось, что тестам тоже нельзя верить
Репетитора не нанимают по резюме. Ему дают тетрадь реального ученика и смотрят не на то, знает ли он ответ, а на то, где он остановится. Подскажет,…
How to implement context decay so an AI agent forgets stale or incorrect instructions over time?
A year into a project, one agent's memory holds three instructions that should no longer win. It says to install packages with npm, and since June i…
How to Build Financial Dashboard Pagination with Traceable Retrieval Contracts
Short answer: use staged retrieval with an explicit collection, bounded queries, and a cursor that carries source context forward. For a financial r…
Close the Loop: Chatbot Analytics That Turn Misses Into Fixes
Many chatbots stall for the same reason. Unanswered questions build up and nothing changes. Teams ship a release and move on. Users try again and gi…
My Eval Said RAG Made Things Up. My Eval Was Wrong.
I maintain django-explain-errors , a Django middleware that catches unhandled exceptions in development and asks an LLM to explain them. It works in…
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…
How to Shape Insurance Claims Retrieval Architecture: 5 Access Rules for Auditable Intake
Short answer: use a staged retrieval design with explicit collections, bounded queries, and source context that survives every handoff. For an insur…
Build a RAG Evaluation Set Before You Ship Your AI Feature
Build a small evaluation set before you ship a RAG feature. That means 50 to 100 real questions, each with an expected answer and the source documen…
Real-Estate Discovery Retrieval: Hosted vs Self-Managed Privacy Controls (Choose Hosted)
Short answer: use a staged retrieval design with explicit collections, bounded queries, and traceable source context; choose a hosted API when your…
Chunking — Why How You Split Documents Decides Retrieval Quality
The previous article explained how embeddings convert text into vectors so similar meanings land close together in vector space. Before you can embe…
I Tested Amazon S3 Vectors' New Pre-Filtering Against Exact Ground Truth
A filtered vector query that asks for 10 results can come back with 2, and nothing errors. AWS's own launch post shows exactly that on a CLASSIC ind…
Hybrid Search and Reranking: What Each One Actually Buys You
Enterprise RAG Engineering — Part 2 of 3 Where Part 1 Left Off Part 1 argued that most enterprise RAG systems fail at the ingestion layer, before a…
Power Up Your Agents: Execution Hooks and Smart Memory in Agent Kernel
By Yaala Labs Ever wished you could intercept your AI agent's thoughts before they speak? Or give them a photographic memory that lasts exactly as l…