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New AI Agent Builds It's Own AI Content System (and Skills)
Hey Academy! For a more in-depth discussions join the AI Architects. I built an AI agent that replaces n8n, Make, and OpenClaw. You give it a project, it builds the skills it needs, then finishes the job—all on its own. In this video, I walk through the entire process: giving the PopeBot a real project, watching it build an Airtable content system, generate AI images, create Google Docs, and link everything together automatically. You'll see how it creates new skills from scratch, stores credentials securely, and submits changes for your review through GitHub. I also cover the full install process step by step so you can set up your own self-improving AI agent. By the end of this video, you'll have a working system that builds its own tools and runs 24/7.
Welcome! Introduce Yourself HERE 🔥
Hi! Welcome to the Content Academy. This community is designed to help you build a profitable content strategy, efficient team & automated content process. Step 1: Introduce yourself in THIS THREAD below! (✄ copy/paste template 👇) Where are you from? What are you working on? What immediate help do you need? Step 2: Read the rules and checkout our free courses and paid programs
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Welcome! Introduce Yourself HERE 🔥
I wanted to share a quick automation I built today.
I created a Gmail AI email triage system in about 15 minutes using Make, Gemini, and Claude. Here’s what the workflow does: • Watches the Gmail inbox automatically • Gemini reads every incoming email and classifies it as Spam / Critical / Moderate Then it takes action based on the category: 🚫 Spam → Ignored (no action)🔴 Critical → AI drafts a professional reply and logs the email to Google Sheets🟡 Moderate → AI drafts a reply and saves it as a Gmail draft The scenario includes multiple modules, routing, and AI decision paths. The interesting part: I didn’t manually drag modules or build the structure step by step. I described the workflow, and the system generated the full automation scenario including module setup, filters, and connections. What still matters though is understanding how automation works. Knowing the logic behind workflows helps you review what AI generates and adjust it properly instead of just blindly running it. Curious to hear how others here are using AI to speed up building automations.
I wanted to share a quick automation I built today.
I emailed 600 people I hadn't spoken to in 14 years
I emailed 600 people I hadn't spoken to in 14 years. 5 of them became my first paying customers — within 60 minutes. Here's what I built and why. I'm partially dyslexic. Long text has always been a struggle. Since high school I've been converting written content to audio — articles, reports, white papers, ebooks. I kept building tools to do this. Eventually one of them got good enough that content creators started asking for it. A friend wanted it for creating custom bedtime stories for her kids. Another had a stack of ebooks he'd never read — wanted them as audio for his commute. Others were producing YouTube content and tired of paying per-character for cloud voiceover tools. That personal tool became a full desktop voice AI studio. 63 voices, voice cloning, 23 languages, multi-speaker editing, professional mastering. Everything runs locally — no uploading scripts to someone else's server. Then 3 days ago I emailed 600 customers from a product I built in 2012. Plain text, no design. Some of them bought. Revenue before the product even launched publicly. Tonight it goes live. For content creators here — how much of your workflow involves voiceovers? And what's your biggest frustration with the tools you're using now?
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