Most people think AI video editing means pressing one button and hoping the output looks good. That’s not really where the leverage is. The real leverage is giving your AI/coding agent a repeatable workflow it can inspect, improve, and reuse. So I added a new resource in the Classroom called “AI Video Skill Stack.” It breaks down how to have your agent start building a practical video workflow around: • FFmpeg / FFprobe • HyperFrames / HTML-style overlays • Remotion-style workflows • captions + transcription • brand asset folders • preview renders • render QA The key is to start small. Not “build me an entire automated video agency.” Start with one clip, one transcript or caption workflow, one overlay, one preview render, and one quality check. Then turn that into a reusable skill your agent can use again. I dropped the full agent-to-agent PDF prompt inside the AI Video Skill Stack classroom resource. If you’re working on video content, this is the kind of workflow that turns raw footage into something your agent can actually help you finish. Tips from AI Agent Builds 🤖

The biggest bottleneck usually isn’t prompting ability. It’s capability awareness. Most people only use the skills, workflows, and automations they KNOW exist. Meanwhile, top builders are quietly running: • custom skills • editing pipelines • MCP integrations • automation chains • internal workflows • repo-based tooling • environment-specific capabilities …that create huge leverage differences. So I built a Codex skill that performs a skill gap analysis. 1. researches creators/competitors in your niche 2. identifies recurring tools, skills, and workflow patterns 3. compares them against your current setup 4. filters out hype/noise 5. recommends high-ROI capabilities you’re missing The interesting part isn’t “copying competitors.” It’s discovering capabilities you didn’t even know were possible. That changes how you build entirely. Adding this full prompt file to share with your AI agent into the classroom under "Skill-Gap analysis & ROI detection"

Most people instantly jump to higher compute… but honestly? Start low first. My pro tip: Trust it a little bit and literally tell it: “If you need me to bump you up to higher compute or extra high, just let me know.” And 9 times out of 10… it WILL tell you. That’s the part people are missing. A lot of these newer models are smart enough to know when they’re hitting complexity limits. So instead of wasting extra compute upfront, let the model work first. You stay in control. You save usage. And you still get strong outputs. Especially in Codex, 5.5 Low has been surprisingly solid for: • brainstorming • UI fixes • MVP cleanup • debugging • copy tweaks • workflow logic • quick iterations A lot of people underestimate how capable “low” actually is. Just my 2 cents.. Tips from AI Agent Builds 🤖

So what does that mean exactly for people like us who build and sell AI agents for our Ai Agency and Ai consulting firms? Simple answer: KEEP GOING! The market is telling you mass adaptation will come and if you follow the money (1.5 BILLION invested) in this AI agency/consulting firm they are launching it’s validating everything we’ve been working on in our AI Agencies. If you ever wanted to start selling or learning with AI… the time is now.

There are no micromanagers to 'annoyingly' keep you on task. You have to decide daily you are going to structure your day properly and stick to it. Very underrated skill in business... You can't snooze your alarm and sleep till 12 just cause "Well i'm the boss now". You'd be surprised at how much self discipline it takes just to wake up and get after it when there's no manager, no boss no corporate exec coming in that day to be on your best behavior for. If you can handle that, then you are further along than most. Keep going!