Business isn't hard because it's complicated. It's hard because it forces you to do the things you don't want to do. Most people never figure this out. They spend years convinced they're missing the perfect strategy, the right tactic, the course that finally unlocks everything. They scroll, they research, they plan. And the whole time, they ignore what's sitting right in front of them — the most basic actions that actually move the needle. Pick up the phone. Make the call. Text the potential client. Create the content. Cut the expenses. Have the brutal conversation about money with your spouse. Tell your kids, "I can't come today." Nobody wants to hear this. I didn't either. The Search for the Secret I wanted the secret plan. I was searching for it — the hidden playbook that successful people weren't sharing. But here's what I learned: I wasn't going to wait for it. And the real breakthroughs in my life didn't come from a new framework or a better funnel. They came from facing fears and making hard choices. From uncomfortable conversations with real people about real things. That's it. That was the whole secret. Why Good Strategies Feel Wrong (after the excitement wheres off) Here's the thing about genuinely good strategies: they're boring and/or scary. They ask you to prioritize two or three actions, repeat them relentlessly, and get zero results at first. That's not a bug — that's the point. Good strategies work because they leverage an insight that no one else can sustain or are scared to do. The insight itself is usually simple. Obvious, even. It's an observation of how the system works and where the opening is. Anyone can see it. Almost nobody can execute it — because execution comes with fear, discomfort, and the constant temptation to quit and go find something easier. That's when it all falls apart for most people. Not at the strategy level. At the feeling level. What Actually Changed for Me I know all of this because I lived it. For a long time, I was the person refreshing my feed looking for the missing piece. Convinced that if I just found the right strategy, things would finally click.

I built my own AI agent, it's called the Pope Bot, and it works kind of like OpenClaw (Moltbot) but with two big differences: it's more secure and way more scalable. Here's the basic idea: You send the bot a task (via API, Telegram, whatever). The bot creates a branch in GitHub with that job. GitHub Actions picks it up, spins up a container, runs the task, and checks everything back into the repo when it's done. Nothing runs on your computer. It runs in the cloud. Your API keys? Stored securely in GitHub Secrets. They get injected at runtime and don't just sit around exposed somewhere. And like OpenClaw it can modify itself. I told it to add a scheduled task (a cron job) to run every 30 minutes. It figured out how to update its own config, pushed the changes back to the repo, and now it just... does that. On its own. It also builds its own tools over time. Say you tell it to check your email. It doesn't have a tool for that yet. So it looks at the API, figures out the call, writes the code, and saves that skill back into the repo. Next time? It already knows how. It only figures it out once. So your bot gets smarter the more you use it. And because everything lives in Git, if you ever wanted to share your assistant with someone, you just share the repo. They swap out their keys and they're exactly where you are. I'm working on getting this out to you all as soon as I can. It's one of those things that's easier to build than explain — but more coming shortly.

🔴 Live Stream – Tuesday, February 3rd at 11 AM >> CALENDAR << I'll be covering four topics I've been digging into lately: 1. OpenClaw (aka Maltbot/Clawdbot) Going beyond the surface on this one — I'll break down the lesser-known underlying framework that powers OpenClaw and what makes it interesting. 2. Remotion.dev + AI Video Orchestration I've been building an MCP that connects to various AI APIs and Airtable to manage assets and orchestrate video creation — scenes, segments, faceless videos, demo videos, etc. I'll walk through what's possible with Remotion as a web-based video editor paired with Claude Code. 3. Running Your Own Local LLM If you're going to have an AI agent/assistant running 24/7, paying for expensive models like Claude around the clock isn't practical. I'll share my thinking on how to set up a local machine running models like DeepSeek or Kimi for always-on tasks, while reserving premium models for when you actually need them. 4. AI Chat Interfaces as a SaaS Framework I built a YouTube Strategist SaaS (thumbnail help, research, etc.) on top of a framework I created for launching chat-based SaaS apps quickly. The idea: instead of designing complex UI for every feature, give an LLM the right tools and let the chat interface handle it. I'll demo the app and walk through the framework. Hope to see you there! 🎙️

Hey Academy! Think about it—Claude Code, WhatsApp bots, Slack agents, every new AI product. They're all chat interfaces. Why? Because it's just easier. Building custom UIs takes forever. But chat? It's universal. It works. And when you DO need a specialized view (like a video player), you're still doing the actual work in the chat. The UI is just for viewing. So here's the problem I ran into... I built some really powerful Claude projects. YouTube title research agents, tools that hit APIs, stuff that actually saves me hours. But I can't sell my Claude project. I can't put a paywall in front of it. Same with GPTs. So I built my own framework. It looks like ChatGPT, but it's not. It's a SaaS shell that lets you: → Build your own agents (like GPTs or Claude projects) → Connect them to backend automations (n8n, APIs, whatever) → Add billing and credits → Actually charge people to use them The agents live in the chat. Users subscribe. You get paid. Whether you're building AI tools for YouTubers, chefs, marketers—doesn't matter. You define the agents, hook up the backend, and monetize. I'm still building this out. If you're interested in something like this, drop your feedback below—I'd love to hear what you'd build with it.

Hey Academy! If you want to learn to built these apps join the No-Code Architects! Stop building traditional apps with confusing interfaces—chat is the future. Every major AI company has moved to chat as their primary UI, and now you can too. In this video, I'll show you how to build a complete AI chatbot SaaS using a free GitHub project, Vercel deployment, and Claude Code. You'll get streaming responses, built-in authentication, and a paywall-ready setup so you can actually monetize your app. But we're not stopping at a basic chatbot. I'll walk you through connecting N8N to give your bot real superpowers—custom tools that call external APIs. As a practical example, we'll build a YouTube viral title generator that analyzes your video script and creates click-worthy titles using real YouTube data. If you want to build profitable AI chat apps, this is your blueprint.