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It’s 2026, and we are seeing new ways to push AI programming to its limits every single day. Today, we’re breaking down the Ralph Wiggum Technique—a method that trades efficiency for sheer, brute-force determination. Named after the optimistic Simpsons character, "Ralph" is essentially a coding agent wrapped in an infinite bash loop. It’s not about being the smartest agent in the room; it’s about being the most persistent. If it hits an error, it loops, reads the error, and fixes it. In this video, I’ll walk you through the core concepts, show you the three files you need to get started (Specs, Fixed Plan, and Prompt), and demo the technique by building a simple "Guess the Number" Python game using the Gemini CLI. In this video, we cover: Why traditional long-context chat agents get "lazy" or hallucinate. How to set up the Ralph loop using a simple bash script. A "Hello World" demo: Building a Python game from scratch. Advanced concepts: Using sub-agents and defining "Standard Libraries" for complex web apps. 🔗 Links & Resources The GitHub Repo (Clone this project): https://github.com/billyjacobson/hell... Geoffrey Huntley's Original Blog Post: https://ghuntley.com/ralph/ Gemini CLI Documentation: https://geminicli.com/ ⏱️ Timestamps 0:00 - Intro: The Ralph Wiggum Technique 0:50 - The Problem: Why AI Agents Get Lazy 1:55 - What is "Ralph"? (Optimistic & Deterministic) 3:30 - The Architecture: It’s Just a Bash Loop 4:50 - The Setup: Specs, Fixed Plan, and Prompt 8:20 - Live Demo: Running the Loop with Gemini CLI 10:50 - Testing the "Guess the Number" Game 11:25 - Advanced Techniques: Standard Libraries & Sub-Agents 13:47 - Real World Example: Podcast Analyzer App 15:20 - Conclusion #AIcoding #Gemini #GoogleCloud #Python #SoftwareEngineering