Ever feel like you're not getting the most out of Claude Code? Here's a methodology that's transforming how developers work with AI assistants. What is it? The Ralph Wiggum Loop is an iterative approach based on Geoffrey Huntley's technique, named after the Simpsons character known for unexpected brilliance. The core insight: single-shot prompting rarely produces optimal results, but intelligent iteration creates magic. Get Started with the Official Repo 🔗 github.com/snarktank/ralph This is the autonomous AI agent loop that runs repeatedly until all PRD items are complete. Each iteration spawns a fresh instance with clean context, while memory persists via git history, progress.txt, and prd.json. How It Works Write a PRD — Define what "done" looks like Run the loop — Ralph executes your task iteratively Persist progress — Git + artifacts maintain state between iterations Repeat until complete — Fresh context each cycle, building on previous work Quick Setup bash# From your project root mkdir -p scripts/ralph cp /path/to/ralph/ralph.sh scripts/ralph/ cp /path/to/ralph/prompt.md scripts/ralph/ chmod +x scripts/ralph/ralph.sh The Philosophy Don't aim for perfect on first try — Let the loop refine the work Failures are informative — "Deterministically bad" means failures are predictable Prompt engineering is key — Success depends on writing good prompts Fresh context is reliability — Each iteration clears context, re-reads specs, plans, and codes Key Tips Set --max-iterations as your safety net (start with 20-30) Include what to do if stuck in your prompt Keep PRD items small enough to complete in one context window Let Ralph update AGENTS.md with learnings for future iterations Why It Works You're not babysitting Claude step-by-step anymore. Define success criteria upfront, then walk away. Solutions that survive multiple iterations are stress-tested far more thoroughly than single-shot generations. Check out the repo and try it on your next project 👇 🔗 github.com/snarktank/ralph

I haven't used my n8n account for some time. Is there an easy? way to determine whether my account is hosted on cloud or self hosted

If you've sold an AI automation to a client, any tool, any industry, I want to hear about it. I'm collecting case studies to break down on the channel. This is your chance to build authority, get your brand out there, and showcase what you've built. 🎁 Bonus: I'll be analyzing all submissions and sharing the trends with you: what's selling, which industries are buying, and where the opportunities are. So even if you don't get featured, you'll benefit from the data. 👉 Fill it out HERE Takes 5 minutes. You can submit multiple projects.

Just discovered @Skool_com 70 days ago, and it’s like reliving my uni hustle—bookkeeping for small shops on the side, building connections that felt like family. In a world gone solo post-COVID, Skool’s genius is bringing back real community while creating ethical entrepreneurs. Shoutout to @Alex Hormozi , @Andrew Kirby @Sam Ovens _, and folks like @Joseph Groom running joyful spaces like Skool Hub. And many many more. Who are contributing to the great community. Loving being part of this—future millionaires in the making .

Hey everyone, Today I actually took a step forward and built my own Voice AI Agent platform which can directly do outbound calls. The idea came up randomly while I was on a Google Meet call with a friend, and instead of overthinking it, I decided to just try building it. In around 3 hours, I managed to set up a basic voice AI agent. It can even make outbound calls, which honestly surprised me a bit. What really stood out was the cost. A 2-minute call costs me around 2.5 cents, which feels crazy when I compare it to tools like Retell that were costing me around 7 cents per minute. It’s still very early and definitely needs improvements and more features, but it already feels fun and promising to build. I haven’t deployed it yet, but I’m planning to keep improving it.