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🔒 Q&A w/ Nate is happening in 15 hours
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🚀New Video: I Tried 100+ Claude Code Skills. These 6 Are The Best.
After 400 hours in Claude Code, I noticed that businesses keep paying for the same six types of skills. In this video, I break down each one, what it does, and why these simple, boring skills are the ones that actually sell. Whether you're brand new to AI automations or already building for clients, these are the skills worth learning first.
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🚀New Video: Build & Sell Claude Code Operating Systems (2+ Hour Course)
This is the full walkthrough of how I build my AI Operating System inside Claude Code, from the frameworks I use to think about it (the Three Ms and the Four Cs) to the actual setup, connections, skills, and routines that run while I sleep. By the end you'll know exactly how to set up your own AIOS, even if you've never opened Claude Code before. The full template, docs, and resources are free in my school community linked below. GITHUB REPO
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🏆 Community Wins Recap | Apr 25 – May 1
From AI roles and first clients to live receptionist systems and enterprise training deals - this week inside AIS+ showed what happens when builders stop watching and start executing. 🚀 Standout Wins of the Week inside AIS+ 👉 @Griffin Maklansky went from being laid off to landing an AI Workflow Builder role in just 1 month. 👉 @Ahmed Bin Faisal landed another $2,000 USD client — an interior design firm — and broke down exactly what led to the close 👉 @Narsis Amin built a working AI restaurant receptionist handling bookings, availability, and CRM logging end-to-end. 👉 @Josh Holladay closed a $4.5K (+$1K) client with half up front today — and dropped his top 10 lessons from the close 👉 @Dion Wang received his first official testimonial, validating real client impact and around 40 hours/month saved. 🎥 Super Win Spotlight | @Duy Nguyen Duy started as an engineer who was curious about AI — but unsure how to turn that curiosity into something real. After joining AIS+, he went from learning passively to building his own AI-operated business, Sharper Automations. Since then, he has: • Built a 24-agent AI business operating system • Landed 2 local paying clients through word-of-mouth • Created a system that improves itself weekly through feedback loops • Started moving toward his goal of leaving his corporate job His biggest shift? From “Can I really do this?” → to building a real business around AI automation.
🏆 Community Wins Recap | Apr 25 – May 1
I cloned a full SaaS frontend in under 10 minutes.
No Figma. No dev handoff. Just Claude. --- 𝗧𝗛𝗘 𝗣𝗥𝗢𝗕𝗟𝗘𝗠 Replicating a polished UI used to take days. Inspect element. Screenshot every section. Brief a designer. Wait. Founders without dev resources just... gave up. --- 𝗧𝗛𝗘 𝗦𝗛𝗜𝗙𝗧 UI cloning is no longer a coding task. It's a prompt-engineering task. --- 𝗛𝗢𝗪 𝗜 𝗗𝗜𝗗 𝗜𝗧 → Open a fresh Claude session. Paste the target URL. → Drop in one screenshot of the sidebar for navigation context. → Ask Claude Opus 4.7 to decompose the full layout into detailed section-by-section prompts. → Wait 4-5 minutes. It returns a complete prompt blueprint. → Paste that blueprint into Claude Design. Answer its clarifying questions. → Watch a functional frontend appear. Total active work: under 10 minutes. --- 𝗧𝗛𝗘 𝗥𝗘𝗦𝗨𝗟𝗧 I cloned app.gojiberry.ai front-to-back. 5 minutes of active input. Zero lines of manual code.
I cloned a full SaaS frontend in under 10 minutes.
I've watched dozens of businesses try to implement AI (And most stall out before they see a dollar of ROI)
Here are 5 things they always underestimate: 1️⃣ Data is never ready ↳ Every company thinks their data is "pretty clean." It never is. Messy sources, missing fields, inconsistent labeling, and access permissions issues will consume more time than the actual AI work. 2️⃣ Infrastructure is not optional ↳ You cannot bolt AI onto broken systems. ETL pipelines, API layers, CRM integrations, and vector databases have to be built before any model works reliably. This is where most projects stall. 3️⃣ Prompt engineering is real work ↳ Hundreds of prompts get tested before anything goes to production. RAG pipelines, guardrails, cost optimization passes. If your team thinks "just type better prompts," they are not ready. 4️⃣ The human side is the hardest part ↳ Internal resistance, retraining staff, and changing workflows take longer than the technical build. You can have a working AI system and still fail because the team will not use it. 5️⃣ ROI takes months, not weeks ↳ Every company that hit $500K in savings and 30% productivity gains had months of iteration behind it. There are no shortcuts. The iceberg is real, and you have to go through it. This is what implementing AI in a real business actually looks like. And every business that's hit real ROI pushed through these phases.
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I've watched dozens of businesses try to implement AI (And most stall out before they see a dollar of ROI)
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