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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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…
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…
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…
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,…
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…
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…
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…
Human Oversight of AI Agents Failed 33% of the Time in Testing
When AI agents ask for permission to act, how often do humans actually catch the dangerous ones? A study on AI agent command approval accuracy acros…
Optimizing LLM Stream Ingestion: Reconstructing Truncated JSON Payloads in 0.0122ms
Every engineering team deploying production-grade LLM agents or RAG pipelines faces the exact same architectural bottleneck: truncated network data…
Top 5 Dev Tools Released in Late July 2026
LangChain 0.3.0 LangChain 0.3.0 is a popular AI framework that enables developers to build applications with large language models through enhanced…
LangChain Essentials — The Only Things You Need Before LangGraph
Note: This article was written in July 2026 using LangChain 0.3.x. APIs may change in future versions — check the LangChain docs if something doesn'…
Handoffs can turn one task into a 15x token bill
Handoffs are useful when a specialist agent needs to take over a task. They also make cost easier to hide, because the bill is spread across graph n…
Delegation Masking: Why Your LangChain Callbacks Lie About Sub-Agent Failures
You delegate a task from Agent A to Agent B in LangChain. Agent B fails. Agent A's callback chain fires 'success' anyway. This is the observability…
Understanding FilesystemBackend in LangChain's Deep Agents
In a previous example, we used StateBackend , where files belonged to a specific LangGraph conversation thread. This time, we are using something di…
AI Agents in Finance Live or Die by Runtime Receipts | Focused Labs
The board wants to see the bottom line of the RFP. Show the receipt. Financial services boards want to know what they get from the spend on AI in La…
Understanding Middleware in Deep Agents (With Runnable Examples)
If you've built even a simple AI agent, you've probably noticed that the "agent loop" itself is deceptively simple: the model gets a message, decide…
LangChain Advanced Patterns: Building Production-Grade AI Systems
Beyond Basic LangChain You've built a simple agent. Now scale it. Production LangChain systems require: Memory management Error handling Performance…
Building a Robust RAG Pipeline Architecture for Production
Answer up front: A RAG pipeline architecture is a set of connected services that ingest raw documents, turn them into embeddings, store them in a ve…
RAG from Scratch with ChromaDB (No LangChain Required)
Frameworks like LangChain are great for moving fast, but they also hide a lot of what's actually happening under the hood. If you want to understand…
We deployed a LangChain agent for a client and it silently failed for two weeks. Here's what we built to make sure it never happens again.
Six weeks ago, a LangChain agent we'd deployed for a B2B client started failing on roughly 30% of its sessions. No exceptions. No 500s. Nothing in t…