My entire life and business now live in one second brain, and Claude Fable understands it better than I do. In this video I walk through my full Claude Fable AI operating system using the four Cs framework: context, connections, capabilities, and cadence. You'll see exactly how my files and folders are set up, how I keep improving it every day, and the usage tips I rely on to get more out of it.

Most YouTubers show you a single path into AI work: start an automation agency → take clients → sell automations. It works. I know because I built an AI automation agency and sold it. But it's not the only way in, and for a lot of you it's not even the best one. I made this video to break down the two real paths: The AI Career Opportunity Nobody is Talking About in 2026 Here's the quick version: Path A is the agency play. You go independent, take clients, build your own practice. Path B is the employment play. You become the most AI-fluent person in the room, and that's who companies want to hire or promote for AI work. If you're already employed, you become the obvious pick when an AI role opens. If you're looking to get hired, or move somewhere better, you walk in with real work instead of just claims. It's the less obvious path, but it's actually the more common one. The employment numbers (see the video) are shocking actually. Watch the full breakdown in the video. Then do one thing for me in the comments because I'm super curious: Tell me which path you are on. A, B, or both. And one line or so on why. I'll be reading these. Nate

Nobody got into marketing to spend their Thursdays formatting spreadsheets. But that is where a lot of teams end up. Not because they are disorganized or under-resourced. Just because the way Meta advertising works right now, a huge portion of the actual time spent is not on thinking or strategy. It is on doing things that, honestly, should not require a human at all. Creating ad variations for a product launch. Checking what competitors are running this week. Writing up a performance summary for a client who wants it by Monday. These are not high-skill tasks. They are repetitive, time-consuming, and they sit right in the middle of every marketing team's week, every single week. And the cost is not just time. Every hour your strategist spends building a report is an hour they are not spending on the next campaign. Every day your creative process takes longer than it should is a testing cycle you did not get to run. Every week your team is manually monitoring competitor ads is a week where the market is moving and you are reacting instead of leading. That gap, between where teams are spending their time and where they should be spending it, is exactly what this system closes. Three AI agents. One generates product ad creatives and copy automatically. One monitors competitor ads from the Facebook Ad Library and surfaces the insights that matter. One pulls your Meta data and builds branded client reports without anyone having to touch a template. The outcome is not just that work gets done faster. It is that your team's actual capacity changes. You can handle more clients without adding headcount. You can run more creative tests without increasing your production timeline. You can give leadership and clients better visibility into performance without that visibility costing you hours to produce. For a CEO or a COO, this is an operational efficiency question. The same output with significantly less overhead. For a CFO, this is a margin question. Marketing is expensive. When a portion of that expense is going toward manual tasks that a system can handle, that is worth looking at.

Anthropic just dropped Computer Use for Claude Code, which lets it natively control your mouse, keyboard, and take screenshots to interact with any app on your desktop. In this video I walk through how to enable it, demo it sending files through ClickUp and controlling my Mac remotely from my phone using Dispatch, and cover the current limitations you should know about. It's in research preview right now but there are already some seriously cool use cases here.

Stop learning n8n in 2026. Seriously. If you’re still trying to learn n8n in 2026, you might be focusing on the wrong thing. In this video, I explain why you should stop learning n8n in 2026 and what you should learn instead. If you’re thinking about learning n8n in 2026, watch this first. I break down why some creators say to stop learning n8n in 2026, what the better alternative is, and how you can stay ahead by learning the right automation skills instead. Enjoy!