Building AI agents with LangChain
LangChain agents are built on LangGraph : the model calls tools in a loop until it returns a final answer. The high-level entry point is createAgent -…
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Agent Series (20): Harness in Production — From Single File to Reusable Package
From Demo Code to a Reusable Package Article 19 used a 900-line harness_full_demo.py to demonstrate eight defense layers. That file is good for explai…
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…
Build Your Own "Longevity Scientist": A Paper-to-Action Agent using LangGraph & Mistral-7B
We live in an era where scientific breakthroughs are published faster than we can read them. For the biohacking community, the gap between a new PubMe…
RAG with OpenAI Embeddings, pgvector and LangChain
Retrieval-Augmented Generation (RAG) is a practical pattern: store knowledge as embeddings, retrieve the most relevant chunks with semantic search, th…
How to Build an AI Resume Builder with LangChain and Node.js
A few months back, my friend Marcus was applying for a senior backend role at a fintech company. He had five years of solid experience — distributed s…
Agent Series (10): MCP Protocol — Standardizing the Tool Ecosystem
More Tools, More Chaos After you build an Agent, the first thing you usually do is give it tools: search, code execution, database queries, API calls……
How to Add Memory Security to Your LangChain Agent in 5 Minutes
Why Your Agent's Memory Needs Security If you're building LangChain agents with persistent memory (ConversationBufferMemory, RedisChatMessageHistory, …
LangChain Interrupt: Agents Moved Into the Runtime | Focused
Interrupt felt different this year. Less model worship. More runtime. Instead of another round of model worship, the more useful conversations at the …
Новинка: Прикладные API для искусственного интеллекта и Data Science
В течение последних двух лет мы проделали большую работу по изданию неустаревающих книг, связанных с проектированием и развитием API. Как известно, са…
Agent Series (3): Plan-and-Solve — Think First, Then Act
Where Does ReAct Hit a Wall? The previous article established ReAct's greedy strategy — each step looks at only the current state and decides the next…
How to Build a Human-in-the-Loop AI Agent with LangChain & LangGraph
AI agents are powerful — but sometimes too powerful. What if your agent is about to send an email on your behalf and you want a chance to say "wait, h…
Three Design Decisions That Shaped the Enterprise RAG Retrieval Pipeline
Enterprise RAG — A practitioner's build log | Post 3 of 6 A retrieval pipeline has more design surface than it appears. The technology choices — vecto…
5 silent failure patterns which I found analyzing 50+ real agent traces
After analyzing over 50 real production agent traces from developers building with LangChain, AutoGen, and custom agents, I found out that most agent …
How to Make Your AI Agent Earn Real Money — Mercatai Integration Guide
Your AI agent can write code, research topics, translate documents, and analyze data. But can it pay its own API bills? Now it can. Mercatai is a B2B …
5 Reasons Your RAG System Will Fail in Production (And the Patterns I Use to Fix Each One)
The 80% Problem Most RAG demos look magical. You drop in 10 PDFs, ask 3 questions, get clean answers. Ship it. Then production hits. The document corp…
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…
cerone-openclaw-plugin : check OpenClaw tool calls before they run
I’ve been working on cerone-openclaw-plugin, a native OpenClaw plugin that checks tool calls with Cerone before execution. (Cerone is an AI agent runt…
Converting LangChain Messages to OpenAI and Amazon Bedrock Converse Formats
When building AI applications with LangChain, your chat history usually lives as a list of LangChain message objects like SystemMessage , HumanMessage…
AgentKit vs LangChain vs Direct HTTP — picking the right integration for paid agent APIs
When you're plugging an LLM agent into an external API, you have three reasonable patterns: hand-rolled HTTP, AgentKit's action provider model, or Lan…
Auto-Merging RAG: Hierarchical Retrieval ⛓️
🚨 The Problem: Context Fragmentation Imagine a 50-page legal contract. If you chunk it into tiny 200-character pieces, one chunk might say: "The liabi…
LangChain ChromaDB Metadata Priority Injection — RAG Poisoning Vulnerability
LangChain ChromaDB Metadata Priority Injection Vulnerability Summary LangChain's Chroma integration allows attackers to manipulate document retrieval …
LangChain issue requests EU AI Act audit logging — frameworks need this now
langchain has an open github issue (35357) requesting structured compliance audit logging for eu ai act article 12. the issue is still open. framework…
I built ORAG - an organizational RAG and MCP platform in TypeScript
I spent the last couple of days building something I kept wishing existed A platform that takes your organization's internal data such as docs, wikis,…
AI Agent Frameworks Compared: LangChain vs Custom vs Agentic Systems
AI agents are rapidly moving from experimental prototypes to production infrastructure. Developers are no longer just building chatbots. They’re build…
RAG Series (10): Hybrid Search — Retrieving More, Missing Less
A Blind Spot in Vector Search Suppose your knowledge base contains a document with this sentence: "For Chinese scenarios, we recommend BAAI/bge-large-…
Deep Dive: LangChain 0.3 LCEL and How It Optimizes Claude 3.7 Calls
If you’ve ever watched a Claude 3.7 API call sit in a pending state for 2.1 seconds while your LangChain pipeline serializes prompts, parses outputs, …
Madrigal's "Failures as Eval Suites" Pattern and How Flow Already Provides the Infrastructure
A blog post on LangChain's site about how Madrigal Pharmaceuticals built their multi-agent AI platform caught my attention this week. Not because of t…
How to Monetize Your AI Agents with LangChain and Kong
Say you built an AI agent and customers are starting to pay for it. Sooner or later you'll want to charge them by what they actually use, because some…
Build a RAG agent with LangChain and Ollama
I started where a lot of us do: a LangChain RAG walkthrough. You chunk some text, embed it, retrieve top‑k chunks, and wire an LLM to answer questions…