10x Your Output With Robust Custom GPTs - AI Fundamentals Course Part 5

By Dan Sanchez · Episode published

If you’ve been experimenting with Custom GPTs, you’ve probably built something simple that handles a specific task. But what if I told you that’s just scratching the surface?

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If you’ve been experimenting with Custom GPTs, you’ve probably built something simple that handles a specific task. But what if I told you that’s just scratching the surface?

I’ve spent months developing what I call “complex GPTs” – AI tools that don’t just handle one small task but execute entire workflows with minimal human input. These aren’t just tools; they’re digital teammates that can save you hours every week.

Simple vs. Complex GPTs: What’s the Difference?

A simple GPT might take a podcast transcript and turn it into a LinkedIn post. That’s useful, but limited.

A complex GPT, on the other hand, might:

  • Research your podcast guest
  • Generate interview angles
  • Craft compelling episode titles
  • Draft the guest invitation email
  • Create show notes with timestamps
  • Generate image prompts for promotional graphics
  • Write social media posts for various platforms
  • Draft a blog post based on the episode

That’s not hypothetical – it’s exactly what my “My Showrunner” GPT does. What used to take me hours (or even days) now happens in about 60 minutes.

The Building Blocks of Complex GPTs

Creating these more sophisticated tools isn’t just about adding more steps (though my current version has 12 steps and counting). It’s about leveraging multiple input and output types:

  1. Diverse inputs: Text prompts, documents, PDFs, spreadsheets, web searches, images, and audio files
  2. Multiple outputs: Text content, code snippets, tables/spreadsheets, and images
  3. Clear step progression: Each step builds on the previous one with decision points
  4. Templates and examples: For every content type it creates

The real power comes from combining these elements into a workflow that mimics what you’d do manually – just 10x faster.

Why Most People Build GPTs Wrong

Here’s a hard truth: most custom GPTs fail because people don’t break down their processes enough.

AI is terrible at figuring out the steps in a complex process on its own, but excellent at executing well-defined smaller steps.

Think of it like the telephone game – with each step, there’s potential for the AI to drift from your original intent. That’s why my instructions are meticulously organized and color-coded:

  • Yellow sections set the role and context
  • Green sections indicate what the GPT is looking for
  • Blue sections outline what actions to take
  • Purple sections tell it when to pause and ask for input
  • Brown sections reference knowledge documents

This level of structure might seem excessive, but it’s what prevents the GPT from going off-track during a 12-step process. Just to be clear, you DO NOT need to color code your instructions to make it work. It’s just something I do keep it better organized and to help you understand how it works.

The Secret: Templates for Everything

One lesson I’ve learned from building dozens of GPTs: never let the AI guess what you want.

For every single content type my GPTs create – whether it’s show notes, social posts, or guest emails – I provide:

  1. A clear template showing the exact structure
  2. A real-world example demonstrating tone and style
  3. Specific constraints to prevent common AI mistakes

This approach eliminates those frustrating moments where the AI delivers something technically correct but not at all what you wanted.

Turning Your Job Into a GPT Workflow

Ready to build your own complex GPT? Start by grabbing a pen and paper to inventory your work:

  1. What tasks do you repeat weekly or monthly?
  2. Which of these follow a consistent process?
  3. What inputs do you typically start with?
  4. What outputs do you need to produce?
  5. What decisions do you make along the way?

The best candidates for complex GPTs are processes that require multiple steps but follow predictable patterns – content creation workflows, data analysis, customer communication sequences, and so on.

If you struggle to break down your process, imagine explaining it to a brilliant intern who lacks common sense. How would you make it foolproof?

This exercise alone will make you better at delegating, whether to AI or humans.

Learning Through Iteration

Here’s the truth about building effective complex GPTs: no one gets it right the first time.

I keep versions of all my instruction sets because I’m constantly refining them. Each test run reveals small improvements I can make. The real learning happens in these iterations – tweaking prompts, adding constraints, clarifying instructions.

This is where you become an AI marketing expert – not from reading articles, but from the hands-on work of training your digital assistant to think like you.

What repetitive marketing workflow are you going to turn into a complex GPT first? Whatever it is, start small, add steps incrementally, and don’t be afraid to revise your instructions dozens of times.

The result will be worth it – turning yourself from a team of one into a team of ten.