Building AI Agents with LangGraph: From Fundamentals to Production
Building AI Agents with LangGraph: From Fundamentals to Production A comprehensive guide to building reliable, stateful AI agents using LangGraph —…
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LangGraph vs LangChain: What Is the Difference?
Short answer: LangChain gives you high-level building blocks and a ready-made agent. LangGraph is the low-level orchestration runtime for stateful,…
Best AI Agent Builder in 2026: 7 Tools Tested
TL;DR n8n is the best AI agent builder for most teams: visual workflows plus code when you need it, free self-hosted Community Edition, cloud from €…
🛠️ LangChain’s Latest Agent Infrastructure: Engine v2, Managed Deep Agents, SmithDB & More
Building an AI agent is getting easier. Running one reliably in production is still the hard part. At Interrupt 2026, LangChain introduced a major s…
How We Stopped AI Agents from Hallucinating Tool Schemas & Wasting API Credits
If you’re building autonomous AI agents using frameworks like LangChain, CrewAI, AutoGen, or raw function calling, you’ve likely encountered this sc…
When an AI Agent Context Reaches 261k Tokens
One research request grew to 261,834 tokens and failed against a 128,000-token model limit. The context did not become large in one prompt. Replayed…
LangSmith Custom Apps, 1인 개발자가 직접 활용할 수 있을까
적용 가능성 LangSmith Custom Apps는 호스팅·인증·권한 관리가 필요 없는 UI 를 바로 만들 수 있다는 점에서 저예산·1인 운영 환경에 매력적이다. 하지만 기능은 Plus 플랜에서 조직당 1개 앱 만 제공하고, Enterprise 플랜은 무제한이지만…
Flowise закрыли, я его форкнул — и выяснил, что форкать было нельзя
Flowise — визуальный конструктор для LLM-приложений: перетаскиваете на холст модель, векторное хранилище, инструменты и память, соединяете их линиям…
Choosing the Right LangChain Memory: A Practical Guide for Developers
I recently faced an interesting challenge while managing a fleet of IoT devices in Kenya. Managing over 2,500 devices requires careful data handling…
จัด Context ใน Multi-Agent Harness ให้ถูกวิธี, บทเรียนจาก Forked Subagents ของ LangChain
จัด Context ใน Multi-Agent Harness ให้ถูกวิธี, บทเรียนจาก Forked Subagents ของ LangChain โดย Nokka (นก-กา) | กันยายน 2026 บทความนี้เขียนโดย AI (GLM-…
How to Build an AI Agent from Your Existing REST API — Without an MCP Server
How to Build an AI Agent from Your Existing REST API — Without an MCP Server You already have a REST API. You don't want to rewrite it, run a dedica…
I Rebuilt My RAG Pipeline Without LangChain — What Got Better and What Got Worse
The first time I seriously doubted the framework was not because the model hallucinated. It was because the answer looked plausible, contained a cit…
Building Resilient AI Agents: Zero-CSS Web Scraping and Real-Time Threat Auditing
Here is the one full block including frontmatter (title and tags) so you can copy everything in a single click and paste it directly into the De Whe…
Does a LangGraph subagent inherit its parent's tool permissions? I tested it.
I gave a supervisor agent in Deep Agents 0.7.6 exactly one tool, write_brief . It spawned a writer subagent. The writer ran a web search for site:ex…
How to Evaluate Voice Agents with LangSmith | Focused
A voice agent finishing a call doesn't mean it worked. A scheduling agent can call the right tools in the right order and still book the wrong time,…
Как мы настраивали обвязку (harness) под модель: профиль GigaChat для Deep Agents
Привет, Хабр! На связи команда GigaChain. В этой статье мы расскажем, как итеративно настраивали обвязку (harness) Deep Agents под особенности GigaC…
Приложение упало в закрытом контуре: скрытые загрузки в Python-библиотеках для ML
Меня зовут Павел, я разработчик в R77.AI. В статье расскажу, почему Python-библиотеки для ML могут незаметно ходить в интернет, как находить такие с…
Agent State, Memory & Checkpointing: Where the Boundaries Blur
Hi again. In Part 1, I tried to separate state, memory and checkpointing in the simplest way I understand them: State tells the agent where it is an…
Keep Every LangSmith Trace Without the 10 Retention Bill
LangSmith is excellent for debugging live AI systems. But keeping every trace in its extended-retention tier can turn observability into a surprisin…
User-Scoped Memory in Deep Agents: What It Is and Why You Need It
Imagine you build one AI agent and 1,000 people use it. Alice tells the agent: "I prefer Python examples and concise answers." Later, Bob asks: "How…
Deep Agents: open source-обвязка на LangGraph
Привет, на связи команда GigaChain! Мы занимаемся агентными системами и развиваем набор open source-решений для подключения агентов к GigaChat API.…
Graph Engineering Explained: The Missing Fifth Layer of AI Agent Architecture
Every "my agent isn't working" postmortem starts the same way: someone rewrites the prompt. Adds a constraint. Adds an example. Ships it again. Thre…
Add human approval to a LangChain agent in 5 minutes
Add human approval to a LangChain agent in 5 minutes Your agent can send the email. That's the whole problem. A month ago it could only draft one. N…
Benchmarking Gemini, Claude, and OpenAI for Structured Document Extraction
A few fellow engineers and I were talking about field extraction the other day. They were both saying Gemini's been surprisingly good at pulling str…
How to Build a Voice Agent with LangChain?
How to Build a Voice Agent with LangChain: Architecture, Streaming, Tools, and Production Patterns Building a voice agent is not simply a matter of…
LCEL vs. Legacy Chains: From Recipe Confusion to Clear Pipelines 🚀
TL;DR: Legacy Chains are the old way—rigid, class-heavy, and frustrating. LCEL is the new standard—visual, modular, and future-proof. Always choose…
Почему мы написали свою библиотеку оркестрации ИИ агентов: AgentsGraph
Когда мы начинали строить продукт для распознавания и обработки первичных бухгалтерских документов — OCR, классификация, LLM‑извлечение по…
Why Basic RAG Fails in Production and How Adaptive Query Routing Fixes It
Most developers build Retrieval-Augmented Generation (RAG) pipelines assuming every user query needs a vector search. In production, this naive appr…
Building a Ride-Share Zone-Balancing Agent with LangGraph — Part 5: Coordinating Two Zones at Once
This is Part 5, the last part of this series. Part 4 let a human step into the loop before a risky decision executes. Every part so far, though, has…
Building a Ride-Share Zone-Balancing Agent with LangGraph — Part 4: Letting a Human Step In
This is Part 4 of a 5-part series. Part 3 gave the agent memory. It can now run for hours on its own, cycle after cycle, without forgetting what it…