This isn't my usual polished demo...

Author

Jeff Sauer
August 13, 2025

In partnership with

When AI fails (and why I'm sharing it anyway)

$3000/month problem I'm solving with AI

I've been avoiding making this video for months.

Not because it doesn't work. But because it only works 50% of the time.

And that's not the kind of polished demo I usually share.

But here's the thing - sometimes the messy experiments teach us more than the perfect ones.

The $3000 Problem

I used to pay $100-200 per video to have someone transcribe my YouTube content and turn it into blog posts.

Multiple brands. Multiple videos per week.

Some months I'd drop $3000 just on transcription and blog writing.

It was expensive. Slow. And completely dependent on other people's schedules.

So I started experimenting with automating the whole process using AI.

The Goal

Take any YouTube video I create and automatically turn it into an expert-written blog post that matches my voice and style.

Complete with:

  • SEO optimization

  • Table of contents

  • Key takeaways

  • Proper formatting

  • WordPress-ready output

Sounds simple, right?

The Reality

It took me over 20 iterations to get something decent.

ChatGPT kept making things up. Pulling from the wrong videos. Creating generic content that sounded nothing like me.

The custom GPT I built was inconsistent. Sometimes brilliant, sometimes completely useless.

I uploaded my existing blog posts to train it. Fed it transcripts. Refined the prompts dozens of times.

When It Works

When everything aligns correctly, it's magic.

I upload an SRT file from my video transcript, and within minutes I get a 1000+ word blog post that actually sounds like me.

Complete with proper keywords, formatting, and all the elements I normally include.

The quality rivals what I used to pay $120 per post for.

The Normalization Step

Here's what most people miss when building AI systems - you can't automate something that isn't proven first.

I see people trying to build complex automations before they've figured out what "good" actually looks like.

That's backwards.

You need to normalize your results. Understand what works and what doesn't. Define your standards.

Only then can you hand it off to be automated properly.

What's Next

This experiment isn't done yet.

The next phase involves building this into a proper N8N automation that works consistently, not just sometimes.

Something my ProfitSchool Pro members can install and use without going through the painful trial-and-error process I just went through.

Because the hard part is done - I've defined what good looks like.

Why I'm Sharing This

Most of the time I show you finished systems that work perfectly.

But there's value in seeing the messy middle. The failures. The iterations.

Because that's where the real learning happens.

And honestly? Even at 50% success rate, this is already saving me time and money.

Watch the full experiment - including all the failures and breakthroughs - in this week's video. You'll see exactly how I'm building this system and where it's heading next.

To Your AI-First Success,
Jeff Sauer


P.S. I've created three ways to help you succeed, depending on how much support you need:

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