Reduce LLM Token Waste in RAG with Markdown
TL;DR Feeding raw HTML to Large Language Models wastes tokens on markup, scripts, and styling. By rendering dynamic web pages in a headless browser an…
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Claude LLM Execution Harnesses, RAG Rerank, & Browser-based Edge AI
Claude LLM Execution Harnesses, RAG Rerank, & Browser-based Edge AI Today's Highlights This week's top stories delve into advanced LLM orchestrati…
Как мы строили eval и автоматизировали оптимизацию AI-агента для умного помощника
Привет! Меня зовут Алексей, я разработчик в Битрикс24. В первой части рассказывал про retrieval-часть нашего RAG для AI-помощника Марты: как мы …
Metadata Filtering Before Vector Search: The Recall Win Nobody Measures
Book: RAG Pocket Guide: Retrieval, Chunking, and Reranking Patterns for Production Also by me: Thinking in Go (2-book series) — Complete Guide to Go P…
Production-Grade RAG: Why Vector Search Isn't Enough (and How Hybrid Search Fills the Gaps)
Imagine your team just deployed a sleek RAG-based docs assistant for the SaaS platform you develop. In testing, it worked flawlessly. It knows your fu…
RAG-Based Testing Series — Part 4: Edge Cases — What Breaks RAG & How to Catch It
RAG-Based Testing Series — Part 4: Edge Cases — What Breaks RAG & How to Catch It "Your users will never read your happy path. They will, however,…
AI Output Provenance for SaaS: Trace Answers Before They Become Liability
An AI answer can look clean, confident, and helpful while hiding the exact detail your team will need later: where did this claim come from? For AI Sa…
Build Your RAG System Right the First Time: 6 Decisions That Make or Break It
After debugging 20+ broken RAG systems, I've identified the 6 decisions that determine whether yours works. Here's how to get each one right. The RAG …
Your vector memory database remembers everything. That’s exactly the issue.
There is a design assumption baked into almost every vector database and AI memory implementation that sounds reasonable until you watch it grow nodes…
I Built a Production RAG System on My M1 Mac for $0
I Built a Production RAG System on My M1 Mac for $0 Most RAG tutorials stop at "it answers questions." But answering questions is table stakes. The re…
Search bug or model bug - testing a RAG system to tell them apart
I'm an automation tester. Usually my job is simple: the same input should give the same output, every time. Language models don't work that way. Ask t…
Benchmarking AI Agents, Gemma 4 On-Device Workflows & AI System Security
Benchmarking AI Agents, Gemma 4 On-Device Workflows & AI System Security Today's Highlights This week, we dive into critical aspects of applied AI…
Securing AI Systems: Red Teaming, Prompt Injection, and Adversarial Testing
Part 6 of a series on building reliable AI systems In the previous parts of this series, we explored: Testing AI systems Evaluation pipelines RAG eval…
How I benchmarked a 100% local RAG pipeline to 9/9 (zero API keys)
Most "chat with your documents" demos work in an afternoon. Then you hit the last 20%: retrieval that misses the right passage, an LLM that confidentl…
Why I Built RAG From Scratch Before Using LangChain
Technical Note #01: Why I Built RAG From Scratch Before Using LangChain Part of the Agentic Finance Beast Technical Notes series Published: June 7, 20…
LangChain + Chroma: Multi-turn RAG Memory and Automated Testing That Turned 2-Hour Bugs Into 5-Minute Fixes
At 1 a.m., the customer group chat exploded: “Does your customer service bot have only a 7-second memory? I just gave it the order number, and the nex…
Add a PASS/WARN/FAIL Quality Gate to Your RAG Pipeline in 30 Seconds
You deployed a RAG chatbot. The answers are vague. You bump the LLM from GPT-3.5 to GPT-4. The answers are still vague. You double the chunk size. Sti…
RAG Retrieval Quality: Are Large Models Really Necessary?
Introduction: The Place of Large Models in RAG and Lingering Questions Retrieval-Augmented Generation (RAG) systems extend the information retrieval c…
What Is a SERP API and Why Do SEO and AI Teams Need One?
Search results look simple from the outside. You type a keyword into Google, Bing, or another search engine, and you get a page of links, snippets, ad…
Dropbox Nova for AI Coding Agents, OpenAI's Codex Sandbox, & Puppeteer MCP Server
Dropbox Nova for AI Coding Agents, OpenAI's Codex Sandbox, & Puppeteer MCP Server Today's Highlights This week, we dive into Dropbox's Nova platfo…
Bridging the Rigidity Gap: Deploying Secure Agentic RAG in Healthcare Governance
In the healthcare industry, data is both an organization's most valuable asset and its most heavily guarded liability. While industries like e-commerc…
LLM Cost Attribution with OTel, Next.js for AI Agents, LLM Security Testing
LLM Cost Attribution with OTel, Next.js for AI Agents, LLM Security Testing Today's Highlights This week, we delve into practical strategies for manag…
Gemma 4 12B Multimodal, AI Copilot Selection, & AI-Optimized Documentation Strategies
Gemma 4 12B Multimodal, AI Copilot Selection, & AI-Optimized Documentation Strategies Today's Highlights Today's top stories delve into a new foun…
I Work in Healthcare Tech. Here's Why I Built a RAG Tool for Clinical Documents.
I didn't set out to build a RAG application. I set out to solve an annoying problem I kept watching happen. I work as a senior software developer in h…
Evals для чайников. Как тестировать AI-агента, чтобы понимать, где именно он ломается
Большинство команд оценивают производительность AI-агентов через end-to-end метрики: success rate, количество токенов, tool usage, стоимость запроса, …
Зачем backend разработчику Python, если он не собирается становиться data scientist
Долго воспринимал Python как язык из соседнего мира. Где то там data science, pandas, ноутбуки, модели, эксперименты. А у меня обычный backend: API, м…
AI Pipeline: Preventing Drift in Production Systems
A common failure pattern in a retrieval-augmented generation (RAG) system is a progressive decline in performance. This decline, which can be difficul…
멀티 에이전트(Multi-agent) AI 시스템 가이드 2026 — 싱글 에이전트와 차이·도입 사례·외주 비용
멀티 에이전트(Multi-agent) AI 시스템은 여러 AI 에이전트가 역할을 분담하고 서로 통신하면서 복잡한 업무를 자율적으로 처리하는 구조다. 한 에이전트가 처음부터 끝까지 처리하는 싱글 에이전트와 달리, 검색·분석·실행·검증을 각각 다른 에이전트가 병렬로 맡고 …
Agent Orchestration & Workflow Automation: Dynamic Workflows, Robust Agent Patterns, and On-Commit AI Code Review
Agent Orchestration & Workflow Automation: Dynamic Workflows, Robust Agent Patterns, and On-Commit AI Code Review Today's Highlights This week's h…
LangGraph Production, RAG Memory Challenges, and AI Agent Patterns
LangGraph Production, RAG Memory Challenges, and AI Agent Patterns Today's Highlights Today's highlights dive into practical LangGraph pipeline constr…