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Must Read for Anyone Starting an AI Business
Hey everyone 👋 I want to make sure you’re truly using what’s inside the Classroom here on Skool — because it isn’t just theoretical content. It’s the proven starting point for building an AI service business in 2026, based on everything I've learned scaling my own 7-figure AI agency. When I first launched my business back in 2022, I was figuring things out in the dark — long days, trial and error, and a lot of mistakes before the real patterns finally emerged. Since then, I’ve worked with 7, 8, and 9-figure clients, helped thousands of people start AI agencies, and studied what separates the people who succeed from the ones who stall. And now the data is clear: There are TWO proven paths people are using to break into AI. All you have to do is choose the path that fits how you think and work. That’s why the very first thing you should do here is go to the Start Here module inside the Classroom. Inside it, you’ll find: - A clear breakdown of the two proven paths - Clarity on how to pick the one that fits you best - Then you'll find your playbook to land your first paid client fast Everything I wish I had when I started — the frameworks, playbooks, lessons, and action plans — is inside this Classroom. And I continue to update it based on what’s working right now. It’s all here for you, step by step. Don’t let this sit in your dashboard like another course. This is the stuff I lived to be where I am right now. If you aren't already, make sure you're following/subscribed to me for my latest content to help you on your journey: → Main Channel: https://www.youtube.com/@LiamOttley → VLOG Channel: https://www.youtube.com/@LiamOttleyVLOGs → Instagram: https://www.instagram.com/liamottley/ → X: https://twitter.com/liamottley_
Building AI Automations for Businesses – Looking for Case Study Partners
🚀 Looking to Build AI Automation Case Studies Hi everyone! I'm an AI Automation Developer currently building AI-powered business automations using n8n, AI agents, APIs, and LLMs. Some of the solutions I've built include: - 🤖 AI Receptionists (Voice & Chat) - 📅 Appointment Booking Automations - 💬 Lead Qualification & Follow-ups - 📧 Email & WhatsApp Automation - 🌐 Business Websites integrated with AI workflows - 🔗 CRM & API Integrations I'm looking to work with a few businesses or agency owners to build real-world case studies. In exchange for a testimonial and honest feedback, I'm happy to help build or improve your automation at no cost if it's a good fit. If you need help automating part of your business—or you're building automation systems and could use an extra hand—I'd love to connect. 📂 Portfolio: https://app.notion.com/p/TARUN-BONTALAKOTI-Business-Automation-Specialist-30c51e62b1f1805dae9fc5be7a691534?source=copy_link Feel free to DM me or leave a comment below!
I built an Agentic OS for Claude Code and it ran itself overnight
I built a mission control dashboard for my entire Claude Code setup, and it ran itself overnight. The problem: dozens of Claude Code sessions across projects, skills buried in terminal history, no way to see what was active. Everything scattered. So I had a single overnight prompt build an Agentic OS. Here's the quick version: → One dashboard for every project, session, agent, and skill → Grouped by category so nothing gets lost → Natural-language recall to find any past session ("the one where I built X") → Rescan and resume any session straight from the UI The recall feature is the one I did not expect to love. Ask for a session from weeks ago, it finds the exact match and lets you jump back in. It reads your Claude projects folder, classifies each session, and surfaces it all in a clean web UI. Send the prompt at night, wake up to a working dashboard. Full tour here if you want to build your own: https://youtu.be/olWkpHYbS1Y Anyone else organizing their AI work in one place, or still living in terminal tabs?
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need help building automations
I need help building automations the sales is easy for me
The cheapest eval you can build is a folder
If you have anything running on a schedule that produces writing, a draft, a summary, a reply, you probably have no way to tell if the quality slipped. It still runs, so nothing alerts. Catching when an automation BREAKS is easy. Catching when it quietly gets WORSE is the hard one. The cheapest fix is not a framework. It is a folder. Every time you catch a bad output, save it. That is it. Once you have ten, you have a test set. Run them back through whenever you change the prompt and see if the same failures come back. Two things I learned doing this on client work. Cap it and rotate, because if the folder only grows it starts dragging the model toward old failure modes. And version the checklist you grade against, because when the rubric changes your old scores stop being comparable and the trend line you were watching quietly breaks. Most people skip this because it feels too simple to count. It is the only version of quality checking that gets better over time instead of just running. Anyone here actually doing this on client builds, or is everyone still eyeballing it?
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