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In this rather mind-blowing episode of Vibe Coding with Steve and Gene, Steve demonstrates Efrit — giving Claude full access to control Emacs. What starts as a simple show-and-tell quickly melts Gene's brain. Steve shows how Claude can get Emacs do basically anything: open info pages, count files, start shells, even generate a Mandelbrot fractals in a buffer. By doing this, the AI has complete access to Emacs's 50-year ecosystem of packages and can orchestrate complex tasks across multiple windows and processes. You can hear Gene's constantly trying to ask questions so he can get his head around what Steve built. Gene also asks Steve to apply the vibe coding loop from the book to this project: Steve emphasizes that "the plan is everything" - proper planning solves most AI coding problems, including instruction following failures, reward hacking, and context window limitations. His approach involved months of iterative refinement, constantly catching the AI when it tried to "cheat" (like building haiku detectors instead of just writing haikus), and gradually building up a stable system that could handle multi-turn conversations reliably. The breakthrough came when he re-architected the entire system around Thorsten Ball's vision of simple agent loops. We suspect you will find this episode to be mind-expanding, when you can control software in a way that is truly conversational and alive — beyond what MCPs can do today. Steve's system demonstrates how vibe coding can create genuinely transformative new things that the world has never seen. As long as you can articulate your vision clearly, are willing to iterate, know have a sense of where the AI boundaries of capabilities are. https://github.com/steveyegge/efrit Pre-order the book here: https://www.amazon.com/Vibe-Coding-Bu... 00:00 Introduction 00:33 Steve's Project: Efrit in Emacs 03:17 Demonstration of Efrit 06:27 Technical Deep Dive: Building Efrit 09:21 The Vibe Coding Loop Explained 14:07 The Importance of Planning in Vibe Coding 20:44 Adding Context to Coding Agents 21:23 Challenges with Multi-Turn Interactions 22:14 Re-Architecting the System 22:48 Creative Vision for Software Development 23:15 Voice Dictation and Testing Challenges 23:40 Integration Tests and Permission Checks 26:40 Context Window Limitations 30:56 Reward Hacking in AI 33:56 Instruction Following Issues 36:18 Show and Tell: Integration Test Results 38:52 Conclusion and Future Plans