Over the last week you might have seen people having a bit of a lightbulb moment about "loops." It kicked off when Boris Cherny, one of the people behind Claude Code, said something like: "I don't prompt Claude anymore. I have loops running. They prompt Claude and figure out what to do. My job is to write loops." In plain terms: instead of sitting there typing prompt after prompt, you set up a system that prompts the AI for you, over and over, until a job is done. You step outside the loop and design it instead. The frustration I see is that everyone's talking about it and nobody's really explaining how, so it feels a bit like a closely guarded secret. However, we can just ask Claude about it. The building blocks are already in the tools (Claude Code has /loop and scheduled routines built in). You don't need to wait for someone to sell you the secret. Stripped right back, a loop is only four things: - a trigger (a time, an event, or a prompt) - an action (the AI does some work) - a check (something decides whether it's actually good enough) - repeat until it's done, then it tells you That "check" is the bit people skip, and it's the bit that stops the whole thing turning into nonsense on repeat. I've written up a plain-English breakdown with a few marketing examples, I've attached it as a PDF below. In the meantime I'm curious: is anyone here already running loops or scheduled tasks? What for, and what's tripped you up? And if you've not touched it yet, what's the one job you'd love to hand off to a loop?

Happy to of recently stumbled onto Ryan via a youtube interview he did with the Koerner Office. Admittedly Im new to the AI scene, but realize its here to stay and am eager to learn alongside you and contribute to the group as best Im able. My career has centered within the aviation world, with beginnings in the USAF. Im 54 now and am excited to learn how to change my future trajectory in a new arena. My wife and I have 3 grown kids and 3 grandsons now. I recently dove into learning digital marketing, and quickly realized being able to leverage AI will be a game changer.

Thanks to those who joined my Free Live Q&A Call today celebrating 1,000 community members! Here is the full recording along with a summary & timestamps. I may do more of these in the future so stay tuned. Enjoy! Meeting Summary - Terminal vs. Visual AI Tools: Ryan explains that while visual apps like Claude Co-work help non-technical teams share files, solo creators build and scale much faster by working directly in the terminal via Claude Code. - Dominating Generative Search: As Google transitions toward default AI Overviews and AI mode, businesses must prioritize securing top-shelf visibility inside AI summaries to control their industry's digital narrative. - The Power of Niche Expertise: Sustainable high-ticket revenue comes from applying AI automation to uncompetitive, multi-billion-dollar industries (like trucking, logistics, or home services) that you already understand better than the average marketer. Key Timestamps: 5:08 – Explaining structural implementation differences between entry-level visual applications and direct terminal development. 6:52 – A structural walk-through detailing automated resource tracking architectures engineered for national service domains. 8:12 – Analyzing Alphabet's search revenue model constraints and how they affect the rolling deployment velocity of native AI search features. 10:28 – Combining automated source extraction and multi-competitor layout analysis within one integrated terminal run. 11:32 – Separating macro-level search strategy files from individual task execution scripts inside target directory layers. 13:40 – Evaluating realism and consistency variables inside state-of-the-art visual generation engines (GPT Image 2). 17:48 – Using anti-slop prompt blocks to filter generic AI marketing filler and maintain clean vocabulary outputs. 19:48 – Managing practical application boundaries by testing system scripts directly inside high-revenue partner enterprises. 24:32 – Developing scalable omnichannel repurposing frameworks that use video assets to build long-term text visibility.