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🔒 Q&A w/ Nate is happening in 10 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
LLM Agents Don’t Need Better Prompts — They Need Orchestrators
Early AI agents felt simple: prompt + tools + loop. Great for demos. Fragile in production. As soon as agents run longer, use memory, call real tools, or need safety and evaluation, prompts stop being enough. The problem isn’t the model — it’s the missing runtime. 👉 That’s where agent orchestration comes in. 🎉 Modern agent systems separate: Context (what the model sees) State (what persists across turns) Execution (what happens next) Tools (how actions are validated) Policies (what’s allowed) Evaluation (what actually happened) This turns agents from clever scripts into reliable systems. ♉ The Open-Source Orchestrators Leading This Shift: ✅ LangChain – the most popular foundation for tools, memory, and chaining ✅ LangGraph – graph-based execution and stateful workflows ✅ AutoGen – strong multi-agent coordination ✅ LlamaIndex – memory- and retrieval-centric orchestration ✅ Haystack – pipelines and routing for RAG systems ✅ CrewAI – role-based agent collaboration ▶️ Each tackles a different slice of the same idea: LLMs need a control plane. The Takeaway ⚙️ Agents are no longer prompts. They’re runtimes. ⚙️ The teams that win won’t have the cleverest prompt — they’ll have the best orchestrator. ⚙️ If you’re building agents and can’t answer where state lives, how execution is controlled, or how behavior is evaluated, you’re still in demo mode. Orchestration is how agents grow up. 📈
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LLM Agents Don’t Need Better Prompts — They Need Orchestrators
I'm wondering if n8n + the ai of n8n isn't easier to build automations than with cloude code?
Just tested n8n's new AI feature. Asked it to build a lead gen workflow – had the whole thing mapped out in under a minute. Just had to connect the APIs. Two things stood out: - Speed: Idea to working flow in 60 seconds - Visual clarity: You see exactly what's happening at every step For 80% of client work (lead gen, CRM sync, email flows), n8n + AI feels faster and cleaner than Claude Code. Curious from people who've built with both: - Where does Claude Code still win? - Hit any walls with n8n's AI builder? - What's your default for client work in 2026?
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I'm wondering if n8n + the ai of n8n isn't easier to build automations than with cloude code?
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