Как научить языковую модель читать транзакции: превращаем историю платежей в базу знаний
Меня зовут Дмитрий Валов, я тимлид команды «Инструменты для банка (агенты)» в Sber AI Lab — Центре практического искусственного интеллекта Сбера. Боль…
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Two Pre-Registered Benchmarks for Audit-Native RAG: RAB (EU AI Act 10/12/19) + LRB (Time-Travel Retrieval)
Most RAG demos answer "what's the right chunk?" Very few can answer the two questions a regulator or an auditor will actually ask: Replay this decisio…
AI Customer Service Chatbot with Demo Link
What I built A small business owner needed an automated customer support system that works 24/7, answering questions based only on their internal poli…
How to make AI answer questions about your documents, by building RAG from scratch
In the previous post , we talked about context windows. The model has a fixed-size desk and everything has to fit on it at once. When too much is on t…
Long-Term Memory for LLM Agents That Works
A support agent tells a customer their plan is still Enterprise, even though finance downgraded it last week. A coding copilot forgets a repo conventi…
The Context Compression Pattern
Pattern Defined Precise Definition: Context Compression is an inference pattern that utilizes a specialized "selector" model or a ranker to distill la…
Built an AI-Powered Spring Boot Log Analyzer Using RAG + Ollama
I've been working on a log analysis platform that helps debug Spring Boot applications by analyzing logs and stack traces using RAG. https://loganalyz…
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…
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…
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…
Building AshaPulse — An AI-Powered Health Assistant for India's Frontline Warriors
NiDaan: Building an Offline AI Diagnostic Assistant for Rural Health Workers in India Building AI that works without internet in places where it matte…
RAG Explained for Beginners: How AI Assistants Stop Making Things Up
I once submitted an essay with three citations that I hadn't personally verified. The AI had suggested them, and they sounded right. None of them exis…
Everyone’s Building AI Agents. Here’s the One I Built for Myself
These days, everyone seems to be building AI agents. So I figured I should probably build one too. But instead of another generic demo, I wanted to so…
RAG SOTA, Agent Harnessing, and Langfuse Observability for AI Frameworks
RAG SOTA, Agent Harnessing, and Langfuse Observability for AI Frameworks Today's Highlights Today's top stories delve into optimizing RAG performance …
RAG SOTA: I Tested 7 Pipelines and Built SEQUOIA (Open Source)
RAG SOTA: I Tested 7 Pipelines and Built SEQUOIA (Open Source) After 20+ hours of compute time on local hardware, I benchmarked 7 RAG configurations a…
I Built a Lightweight Python RAG Orchestrator That Works with SQLite, PGVector and Qdrant
Most RAG frameworks today assume: a huge dependency graph mandatory LLM orchestration opinionated pipelines complex configuration But many real-world …
I Built an Open-Source Multi-Agent Fact-Checker — Here's How It Works
Problem Statement We have a misinformation problem. But more specifically, we have a speed problem. A journalist spots a suspicious claim. They search…
The SilentRecon Agent Loop Architecture: How We Build AI That Doesn’t Stall
When people talk about “AI agents,” they imagine something autonomous, intelligent, and reliable. In reality, most agents collapse under their own wei…
Vector‑native RAG on Oracle: embeddings, HNSW/IVF, and hybrid search under database governance
Key Takeaways Storing vectors in an Oracle VECTOR column alongside content, metadata, and provenance means retrieval happens inside the database. Exis…
AI Basics You MUST Understand Before Building AI Agent
Many developers are jumping directly into AI agent frameworks like: LangChain CrewAI LangGraph But without understanding the foundations first, things…
The Hardest Part Of Building A RAG App Wasn’t The AI
I almost didn’t start this project. I kept thinking: “I should learn more backend first.” “I should understand AI properly first.” “I should probably …
Building KernelMind Part 3: Evaluation, Retrieval Ablations, RAGAS, and Turning The Project Into Something Measurable
By this point, KernelMind had already evolved far beyond the original “embeddings over code” idea. The system now had: AST-aware chunking fully qualif…
AI Agents Observability, Python Logging for OTel, & PySpark Code Linter
AI Agents Observability, Python Logging for OTel, & PySpark Code Linter Today's Highlights This week's highlights focus on critical tooling and ob…
LLM Wiki - Compiled Knowledge That RAG Cannot Replace
The premise is simple: compiled knowledge is more reusable than retrieved fragments. RAG became the default answer to a straightforward question - how…
Retrieval vs Representation in Knowledge Systems
Most modern knowledge systems optimize retrieval, and that is understandable. Search is visible, easy to demo, and feels magical when it works. Type a…
Reducing LLM Hallucinations in 2026: LoRA, F-DPO, and the Math That Actually Works
It is May 2026, and the field has stopped pretending hallucinations are going to disappear. What has happened instead is more interesting. Researchers…
RAG Series (17): Agentic RAG — Giving the Agent Control Over Retrieval
The Silent Failure of Pipeline RAG Every article in this series has been trying to answer the same question: how do we make retrieval better? Better c…
LLM Persistent Memory & Python Tooling Elevate AI Agent Workflows
LLM Persistent Memory & Python Tooling Elevate AI Agent Workflows Today's Highlights This week highlights practical advances in AI agent developme…
RAG - Sliding Window, Token Based Chunking and PDF Chunking Packages
Sliding Window Chunking Sliding Window Chunking is a more intensive chunking mechanism. In this method, a window size is defined based on a character …