I'm Done Making AI Demos to Focus on the Opportunity of a Lifetime.

Most AI demos are a lie, because making AI actually work is a lot more boring than it sounds. And the ones most likely to win in this era aren't the tech giants. They are the everyday companies who represent 99.9% of the economy.

I say that as someone who makes demos for a living. 90% of my YouTube channel is basically me saying, "Look what this tool can do!" Those videos are great for inspiration, but there's a massive problem with the "demo" format: It makes you think you're finished once the output looks decent.

You aren't.

A demo proves a tool works once, in a vacuum, with perfect data. But in the real world? You try to use that same prompt at work and it immediately falls apart. The info you need is buried in five different apps, half of it is outdated, and your coworkers don't trust the results anyway.

You end up spending more time "fixing" the AI than you would have just doing the work manually.

The AI Chasm: going from demo to production is where most teams get stuck.

That's why I'm shifting my approach. I'm tired of the "clean" version. I want to talk about the messy middle. The boring, unsexy implementation that happens after the video ends. Because in my experience, that's the only part that actually matters.

The Opportunity of a Lifetime (for the 99%)

Most AI content lives in a Silicon Valley bubble, but the economy runs on "normal" businesses.

I'm talking about the 99.9% of companies that represent two-thirds of all new jobs. These are the teams I'm on a mission to help. While massive enterprises spend three years trying to approve a "2% optimization" project, you can move in a weekend.

The smartest money in the world already sees this. Look at General Catalyst. They are currently betting billions on this exact play, buying up "normal" companies with the goal of doubling EBITDA margins within 12 months just by fixing operations with AI.

Here's the best part: You don't need VC money to do this. You don't even need a massive budget. You just need to stop looking for the "magic" and start looking for the friction.

The "Boring" Truth About Success

AI isn't going to take your job, but it should definitely be taking the parts of your job that make you want to quit.

The biggest mistake I see teams make isn't a technical one. They fail because they try to "automate a department." That's too big. Instead, you need one simple rule: Start with the work you already hate.

If you have to do it every day, and you procrastinate on it every time, that's your target. Nobody needs a "culture shift" or a motivational speech to stop doing a task they despise.

A Quick Reality Check

I recently worked with a sales team that was losing 4 hours a day to "detective work." Two hours scrolling LinkedIn for signals, and another two hours staring at a blank screen trying to figure out what to say.

That's not selling. That's just draining your battery before the real work even starts.

We didn't build a "Sales Bot." We just attacked the friction:

1. Automated the signal tracking.
2. Pulled their "tribal knowledge" out of people's heads and into a playbook.
3. Spent weeks fixing the stuff that broke (because it always breaks at first).

The result? They got 20% of their time back. The reps were less fried, and the outreach actually felt human because they finally had the energy to make it that way.

Why I'm Launching "Business AI Explained"

Demos aren't the bottleneck anymore. Execution is.

I'm starting this podcast because I want to have the conversations that don't fit into a 10-minute "how-to" video. I'm talking to founders and operators who are actually running this stuff in normal, messy businesses. No jargon, no hype. Just what's working.

The first three episodes are live now:

Episode 1, Abraham Gomez (Google): Most people overthink data. Abraham shows you how to stop waiting for a "data strategy" and connect AI to your actual spreadsheets and docs in under 30 minutes to see what's actually possible.

Episode 2, Eliott Wertheimer (VanMoof): If you're a founder or manager, you're likely drowning in updates. Eliott breaks down how he uses AI to summarize team progress (Asana/Slack) so he never walks into a meeting feeling behind again.

Episode 3, David Arnoux: The "3/1 ratio." David shares a framework for scaling your output by training 3 people to master the tools while 1 person sets the quality standard. It's the blueprint for delivering enterprise-level work with a tiny team.

How to Start (Today)

Don't overthink the "strategy." Pick one task you're supposed to do today. Something you're currently avoiding because it's tedious. Try to delete it with AI.

That's the whole game. Once you win once, you'll never want to go back.

Check out the show here:

Business AI Explained officially drops Tuesday, Feb 24.