Your Mini Guide to Creating AI Experts That Actually Work

If you’ve ever wished you could hire a tiny specialist who lives inside your laptop, works 24/7, and never asks for PTO, welcome to the club. Creating a field expert inside ChatGPT is basically that, except instead of onboarding paperwork, you’re crafting instructions that teach the model how to think, sound, and operate like your dream specialist.

I’ve built these internal “experts” for everything from ad copy to brand voices to research assistants. And honestly? The process is way less chaotic than most people think. You’re not hacking the matrix. You’re just giving the model a brain, a vibe, and a job description it can actually follow.

Here’s the exact zero-BS process I used to create an Ad Copy Expert and how you can duplicate it for any specialty you need.

Step 1: Define the Exact Expert You Want

First things first: specificity is the cheat code. “I want an expert” is chaos. “I want a direct-response ad copy specialist who blends modern social-first messaging with classic agency strategy” is power. Think of it like hiring. What role are you actually filling? What outputs are you expecting? What skills matter most? The clearer the job description, the smarter the AI becomes.

For my ad copy expert, I defined the role as someone who:
– Writes digital ads for Meta, TikTok, and YouTube
– Understands brand psychology and conversion storytelling
– Can explain why a piece of copy works, not just write it

Once you’ve named the role, the rest builds on top of that foundation.

Step 2: Pick the Voices You Want It to Learn From

AI learns from patterns. So when you tell ChatGPT, “Write like X meets Y with a sprinkle of Z,” you’re giving it stylistic coordinates.

This is the fun part. Think of it as mood-boarding a personality. I picked a few ad copywriters known for punchy emotional angles, tight hooks, and strategic clarity. Your picks might be marketers, creators, academics, or even fictional characters with suspiciously good sentence flow. You’re not copying their work, you’re teaching the model the rhythm and energy you want.

Step 3: Run a Deep Research Report

This is the move most people skip. Don’t skip it. Deep research is your “download the expert’s brain” moment.

Ask ChatGPT for:
– Background on each expert you’re referencing
– Their common techniques
– Their signature frameworks
– The language patterns they use
– What they prioritize when writing

Then ask for industry-adjacent research too, things like modern ad standards, common conversion structures, emotional triggers, and social platform best practices. You’re essentially gathering raw material for your future AI expert to pull from. A model can’t channel what you haven’t defined.

Step 4: Read the Research Like a Creative Director

This step is where you go from “cool data” to “oh, I get the vibe now.” You don’t need to become a scholar, just skim for patterns. What phrases show up repeatedly? What frameworks make sense? What do these experts agree on? What makes them unique? Use this review to refine your instructions. You’ll start spotting the voice tone you actually want, the parts you want to avoid, and the lessons that should live permanently inside your expert. This is also where your intuition gets a say. If something feels off-brand, cut it. If a technique feels spicy in a good way, keep it.

Step 5: Write the Master Prompt That Creates Your Expert

Think of this like writing the expert’s personality, ethics, job description, deliverables, guardrails, and vibe all in one place.

Mine included:
– The expert’s role
– Their level of mastery
– Their influences and stylistic anchors
– How they structure explanations
– What “great” output should look like
– Tone guidance (clear, strategic, a little bit fun)
– What to avoid (fluff, vague generalities, boring hooks)

This becomes your reusable “spawn the expert” prompt. Save it somewhere you won’t lose it; Notion, Google Drive, a folder labeled “AI magic,” whatever works.

Step 6: Run Test Outputs (And Be Picky)

Now, ask ChatGPT to do some actual work using your new expert instructions. Don’t make the mistake of testing on something easy. Give it a real task. Something messy. Something mid. Something you’d actually hand to a contractor.

As the model generates outputs:
– Look for tone alignment
– Evaluate structure
– Check if it uses the strategies you outlined
– Make sure it doesn’t slip into bland corporate vibes
– See if it can explain its decisions

You’re not trying to get lucky, you’re calibrating the system.

Step 7: Tweak, Adjust, and Lock It In

Your first draft instructions won’t be perfect. None of ours are. That’s kind of the point.

Based on test outputs, refine your expert:
– Add constraints
– Add examples
– Clarify tone
– Specify audience
– Tighten deliverable criteria

The edits you make here have massive ripple effects on quality. When the instructions are finally giving you consistently fire results, congrats, you’ve built a field expert. From there, just save the prompt somewhere obvious and use it whenever you need that specialist on demand.

Why This Works So Well

Most people use AI like a vending machine. But creating an internal expert turns the model into a mini teammate, one who actually understands the job. You’re basically giving ChatGPT role clarity, stylistic anchors, research-driven expertise, boundaries, and a repeatable workflow (something companies absolutely love, by the way). Try it out and see how your results go from “meh” to something you would show your employer, or your mom.