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🔒 Q&A w/ Nate is happening in 3 days
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🚀New Video: GPT-6 Astra FINALLY Kills AI Website Slop
GPT-6 Astra might be the new AI design king. I tested it on one-shot websites, HyperFrames motion graphics, and a 152 GB event-footage recap, then broke down what helped it avoid the usual AI design slop. You’ll see how brand guidelines, the Pain-Person-Promise framework, strong inspiration, and my Scrollcraft skill changed the results. SCROLL-CRAFT SKILL
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Have you sold an AI or Claude system?
I’m researching the AI systems people are successfully selling right now, including what they built, who bought it, and how much they charged. I would love to make a YouTube video about this to be able to share this data with you guys! And feature some of you in the vid. The more detail you provide and the stronger your proof, the more likely your submission is to be featured. Submit your system here: https://forms.gle/H2bhTQn1x7gBkTx26 Submit the form again if you have multiple distinct systems to share.
Have you sold an AI or Claude system?
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🏆 Weekly Wins Recap | August 29 – September 4
From first law-firm clients and $6K + MRR pipelines to outage-proof AI systems and explosive audience growth, this week inside AIS+ showed that real work keeps paying off. 🚀 Standout Wins of the Week inside AIS+ 👉 @Ryan Cunningham turned 2 free case studies into a potential $6K build + $1K MRR pipeline, showing how proving value first can open the door to paid work. 👉 @Glenn Meleder turned a warm reach-out into his first client project, building email triage automation and a local AI Brain for a law firm. 👉 @Harshit Kumar automated a 300-keyword weekly SEO report for a client, eliminating around 6 hours of manual work every single week. 👉 @Tanya Maslach grew from 72 to 20K+ Instagram followers in just 2 weeks, with one post reaching 2.5M views and 350K interactions. 👉 @Mike AI Consultant built his AIOS with enough redundancy that his client work kept running even when major AI providers went down. ⸻ 🎥 Super Win Spotlight | @Bruce Harrison Bruce joined AIS+ with a non-technical background and quickly realized something important: Knowing how to build AI systems wasn’t enough. He also needed to learn how to explain the value, earn trust, and communicate with business owners in language they actually understand. That shift helped him land interviews with Fortune 500 companies and step confidently into higher-level discovery conversations. He even says he gained more practical value from AIS+ than from a certification program that cost him nearly $5,000. His biggest takeaway? Don’t just learn how to build. Learn how to communicate, sell the outcome, and earn the trust to implement it. 🎥 Watch Bruce’s story 👇 ✨ Building the system is only half the game. Inside AI Automation Society Plus, members are learning how to turn those skills into real conversations, clients, and opportunities.
🏆 Weekly Wins Recap | August 29 – September 4
🔥 What’s One Task You Wish AI Could Do for You?
If you could automate ONE task in your business today… what would it be? ● Lead follow-ups? ● Customer support? ● Appointment booking? ● Content creation? ● Data entry? ● Sales outreach? I’m curious because I’m realizing something: The biggest advantage of AI automation isn’t doing MORE work. It’s eliminating the repetitive work you shouldn’t be doing manually in the first place. So let’s make this a useful thread Comment ONE task you currently do manually. I’ll reply with an AI automation idea that could potentially simplify it. Let’s learn from each other and build smarter systems. 🤝
When Does an AI Assistant Become an AI Operating System?
Here's the question I've been thinking about: Is an AI OS just a powerful assistant? I don't think so. An assistant primarily responds to you. An operating system coordinates what happens around you. That's a very different job. The Line Might Be Autonomy of Coordination An assistant: → You ask → AI reasons → AI responds → Task ends An AI OS: → Detects an event → Understands context → Determines what needs attention → Selects capabilities → Executes work → Updates state → Monitors the result → Decides what happens next You don't have to be the API call. Think About What an OS Actually Owns Not just intelligence. It needs some combination of: 🧠 Context What does the system know? 🗃️ State What has happened, what is pending, and what changed? 🛠️ Capabilities What can the system actually do? 🔐 Permissions What is it allowed to do? 📋 Policies What rules constrain its decisions? 🔀 Orchestration Which agent, workflow, or tool should act? ⏰ Events & Triggers What should happen without being explicitly asked? 🔄 Recovery What happens when something fails? 👤 Human Control When should a person approve, override, or take over? That's starting to look less like a chatbot, AND more like an operating environment for intelligence. Here's the Test I'd Use Ask five questions: 1. Does it maintain state? Or does every conversation start from zero? 2. Can it initiate work? Or does it only respond to prompts? 3. Can it coordinate capabilities? Agents, tools, workflows, data, memory? 4. Does it enforce boundaries? Permissions, policies, escalation, approvals? 5. Can it recover? If something fails, can it detect, contain, retry, rollback, or escalate? If the answer is mostly yes, Maybe you're no longer building an assistant. You're building an AI operating system. And Here's the Weird Part The “OS” may not actually be the model. The model could eventually become replaceable. Claude today. GPT tomorrow. Another model next year. The durable layer may instead be: STATE + MEMORY + POLICIES + CAPABILITIES + ORCHESTRATION + CONTROL
When Does an AI Assistant Become an AI Operating System?
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