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🔒 Q&A w/ Nate is happening in 4 days
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🚀New Video: Claude Code Skills Just Got Even Better
2 videos in one day?? Had to do it... Claude Code just dropped a major update to how skills work. The new Skill Creator helps you build better skills from scratch, run evals to test how they perform, optimize existing skills for better accuracy, and trigger them more reliably. In this video, I break down everything that changed and then do a full live build of a brand new skill so you can see exactly how it works. Whether you're just getting started with Claude Code or you've already been building skills, this update makes the whole workflow significantly better.
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🚀New Video: Turn Claude Code Into Your Executive Assistant in 27 Mins
In this video, I walk you through exactly how I built my own AI executive assistant using Claude Code, and how you can do the same. We go through four phases: setting up the project, adding context and rules, building out your first skills and sub-agents, and how to let it grow over time by layering in more skills, memory, and context as your needs evolve. By the end, you'll have a clear blueprint for setting up a personal AI assistant that actually works the way you work, not just a generic chatbot, but something that knows your business, follows your systems, and gets smarter the more you use it.
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🏆 Weekly Wins Recap | Feb 21 – Feb 27
SaaS builds. $16K contracts. First clients. Outbound systems going live. This week inside AIS+ was all about leverage turning into real results. Here are a few standout wins inside AIS+ 👇 👉 @Michael Elliott landed a $16.8K contract in just 10 hours of work using Claude Code. 👉 @Krishna A closed another $2,000 deal - now $4K+ this year building apps, agents, and SaaS. 👉 @Viktorio Halcu secured his first client on commission, building an AI outbound calling agent. 👉 @Ahmad Abd Alkarim built his first full vibe-coded SaaS with multi-tenant authentication and dashboard systems. 👉 @Mike Thomson launched Outreach Dashboard v2 - full cold email infrastructure stack live and ready to scale. 🎥 Super Win Spotlight: @Mike Thomson | Systems Before Scale Mike didn’t join looking for magic. He joined because he saw people actually building. After testing multiple systems, he rebuilt his entire cold outreach infrastructure using insights shared inside AIS+. Domains. Inboxes. Warmup. Follow-ups. Automation stack ready. Now he’s weeks away from launching outreach at scale. Mike’s journey is proof that you don’t need hype - you need systems, consistency, and the right room. 🎥 Watch Mike's story 👇 ✨ Want to see wins like this every week? Step inside AI Automation Society Plus and start building assets that compound 🚀
🏆 Weekly Wins Recap | Feb 21 – Feb 27
Predictable growth is impossible without pipeline visibility
​A hard truth about scaling an agency or service business: If you are using 5 different tools to manage a single prospect's journey, you are flying blind. ​You can't optimize a sales process when your lead capture data, email open rates, and appointment booking stats are siloed across different platforms. ​This is where the architecture of GoHighLevel becomes a massive operational moat. ​By consolidating the Funnels, CRM, Automations, and Scheduling into one native environment, you stop hunting for data. You get absolute visibility over the entire lifecycle of a lead. ​When every touchpoint is tracked in one place, and every follow-up is automated natively, revenue stops being a guessing game and becomes a mathematical formula. ​Tools are easily replaced. But a perfectly mapped operational system is what actually creates scale. ​Are you running your operations through an all-in-one ecosystem right now, or are you still juggling a fragmented tech stack?
Why perfectionism is ruining your deployments
​I see so many builders get stuck in the sandbox environment. They spend weeks trying to build the "perfect" 50-node n8n workflow, obsessing over every possible edge case and error handler before pushing it live. ​The harsh reality of building operational systems: If you wait until you feel 100% ready, your architecture is already obsolete. ​Real data is messy. Real human inputs break things. You will never predict every error in a test environment. ​The goal isn't to build a flawless V1. The goal is to deploy a functional V1, let the real-world data break it, read the error logs, and iterate. ​Stop chasing the perfect architecture in theory. Chase consistent deployments in reality. ​ How long do you typically test a workflow before finally pushing it into production?
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AI Automation Society
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