Why Top AI Engineers Don't Use LangChain

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Most successful AI companies don't use frameworks like LangChain to build AI agents and there's a very good reason why. Octomind dropped LangChain after 12 months in production, making their code simpler and cheaper to run. The truth is, most AI frameworks are just costly and complex abstractions that can teach you the wrong things and leave you stuck.

In this video, you'll learn how to build real AI agents using the approach the top 10% of engineers use: writing good Python code and calling AI APIs directly. No complex frameworks required, just clean, maintainable code that you fully control.

What You'll Learn:
- Why Anthropic says top AI companies avoid frameworks
- How the agentic loop actually works (the simplest explanation on the web)
- Building a real transcript processing agent with multiple tools
- How Python controls tool execution (not the LLM)
- Why language models can't execute code - they only output instructions
- Creating safe, reliable AI agents with proper validation
- Working with tool calling using Claude and OpenRouter
- The mental model that separates good AI engineers from the rest

Timestamps:
0:00 Why frameworks are holding you back
0:34 Agentic Demo
1:39 Explaining the Agentic Loop
5:24 Breaking down the Python code
10:28 Mental model for top 1% AI Agent

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