Articles, one at a time.
Every piece here was commissioned, drafted, reviewed in public, and merged. No content mills, no auto-published slop.
LangGraph + MCP: Build a Supervisor Multi-Agent System
Build a LangGraph supervisor multi-agent system with live MCP tool servers. Covers langchain-mcp-adapters, MultiServerMCPClient, and checkpointing in Python.
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MCP Code Execution: Build Token-Efficient AI Agents
Cut AI agent token usage by up to 98% using MCP code execution. Learn the CE-MCP pattern, Cloudflare Code Mode, and security trade-offs.
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VS Code Agent Mode in 2026: Companion App and MCP
VS Code's April 2026 releases shipped a Companion App, terminal session agents, and MCP server bridging. Here's what changed and how to use it.
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E2B Sandbox: Secure Code Execution for AI Agents
Add secure sandboxed code execution to any AI agent with E2B. Firecracker microVM isolation, 150ms cold starts, Python/JS SDKs, MCP support.
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Microsoft Agent Governance Toolkit: Developer Setup Guide
Install and integrate Microsoft's open-source Agent Governance Toolkit. Policy enforcement, EU AI Act compliance, LangChain and CrewAI integration guide.
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Mistral Vibe Remote Agents: Medium 3.5 Developer Guide
Run async coding agents in the cloud with Mistral Medium 3.5 (77.6% SWE-Bench). Open PRs, connect GitHub/Linear/Jira, self-host 128B open weights.
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Build an AI Agent with MCP and TypeScript in 2026
Build a Claude-powered TypeScript AI agent that connects to MCP servers, discovers tools, and routes tool_use requests through the MCP client API.
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Claude Design and Claude Routines: Anthropic's New Agentic Products
Everything developers need to know about Claude Design (AI visuals) and Claude Routines (autonomous cloud agents), both launched April 2026.
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Google TPU 8i: What the Inference Chip Split Means for Developers
Google announced TPU 8i and TPU 8t at Cloud Next 2026. This guide explains what the inference-dedicated chip means for LLM cost, latency, and agentic workloads.
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Mistral Large 3: The 675B Open-Weight MoE Model Developer Guide
Mistral Large 3 is a 675B sparse MoE model with Apache 2.0 license, 256K context, and $0.50/$1.50 per 1M tokens. Here's what matters for developers in 2026.
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Qwen3-Coder: 27B Dense Model That Beats 397B MoE (2026)
Qwen3.6-27B delivers flagship-level agentic coding in 27B dense parameters, outperforming 397B MoE models. Apache 2.0 local deployment guide.
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RAGFlow: Self-Host a Deep-Document RAG Engine
Step-by-step guide to self-hosting RAGFlow v0.25 with Docker Compose — deep document understanding, chunking strategies, MCP server, and the Python SDK.
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