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Explore LangChain Open-Sourced Claude Code (Works With ANY Model) with 12,580 views, 357 likes, and 19 comments. Experience the impact of this video content that has captured audience attention.

What is the actual secret behind viral AI agents like Claude Code, Manus, and OpenAI Deep Research? Discover how LangChain reverse-engineered the ultimate agentic harness to create "Deep Agents"—an open-source framework that lets you run a Claude Code-style coding agent using ANY language model (OpenAI, Gemini, DeepSeek, or local LLMs via Ollama). In this video, Cloud Codes breaks down the system design of LangChain's Agent 2.0 architecture. We explore why traditional "shallow agents" get stuck in infinite loops, and how Harrison Chase and the LangChain team solved it using 4 simple ingredients: Detailed Prompts, Sub-Agents, a Virtual File System, and a Planning Tool. We reveal the shocking truth about Context Engineering (why the agent's Planning Tool is actually a "No-Op"), how the durable LangGraph runtime prevents crashes during multi-hour tasks, and how to use the `create_deep_agent` function to build your own production-grade agent. Finally, we give an honest verdict on whether this open-source stack can truly kill Anthropic's tightly integrated Claude Code. ⏱️ TIMESTAMPS: 00:00 - The magic isn't the model, it's the "harness" 00:43 - LangChain clones Claude Code (deepagents) 01:05 - The 4 secret ingredients of a "deep agent" 04:10 - Ingredient 1: The system prompt 04:26 - Ingredient 2: The planning tool 04:40 - Ingredient 3: Isolated sub-agents 04:53 - Ingredient 4: The file system (external memory) 07:30 - Why the planning tool is actually a "no-op" 08:10 - LangGraph: The durable runtime underneath 08:40 - The killer feature: Swapping to any model 09:03 - How to build it in one line of code 11:30 - The open-source terminal agent alternative 13:42 - The harness is the real product, not the model #langchain #claude #claudecode #aiagents #systemdesign #softwareengineering #machinelearning #cloudcodes #langgraph #opensource 🔗 LangChain Deep Agents (Python) https://github.com/langchain-ai/deepagents 🔗 LangChain Deep Agents (JavaScript) https://github.com/langchain-ai/deepagentsjs 🔗 Deep Agents From Scratch https://github.com/langchain-ai/deep-agents-from-scratch 🔗 Deep Agents UI https://github.com/langchain-ai/deep-agents-ui 🔗 Official Deep Agents Documentation https://docs.langchain.com/oss/python/deepagents/overview 🔗 Deep Agents Quickstart https://docs.langchain.com/oss/python/deepagents/quickstart 🔗 Deep Agents Code (Claude Code Alternative) https://docs.langchain.com/oss/python/deepagents/code/overview 🔗 LangGraph https://github.com/langchain-ai/langgraph 🔗 LangChain https://github.com/langchain-ai/langchain 🔔 Subscribe: https://www.youtube.com/channel/UC0DZj1PNa_Fp0MU6uPSKv5w?sub_confirmation=1 💙 Become a Member: https://www.youtube.com/channel/UC0DZj1PNa_Fp0MU6uPSKv5w/join 🐦 Twitter/X: https://x.com/cloud_codes 💬 Discord: https://discord.gg/HVnH9SY48 User Queries: langchain deep agents tutorial how to build an ai coding agent claude code open source alternative openai deep research clone tutorial langgraph agentic workflow system design context engineering vs prompt engineering how to run claude code with local models what is a deep agent ai langchain agent 2.0 release model context protocol mcp langchain

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