If you’ve ever wondered whether artificial intelligence tools like ChatGPT and Claude can do more than write emails or summarize PDFs – they can. I turned prompt engineering into a real business in the US. And it all started with a single well-structured chatbot session. That prompt stack now earns me $150K/year. No coding, no ad spend, no team. Just AI, precision, and clarity.
Before you go, this next article might answer your next question.
What Prompt Engineering Really Means in 2025
Forget the buzzwords. Prompt engineering today isn’t about writing fancy instructions – it’s about systems. It’s the art of turning vague ideas into step-by-step deliverables using language.
You’re not asking the chatbot to “write a business plan.”
You’re building a layered prompt that:
- Defines the product and audience
- Injects tone and structure
- Outlines components and delivery formats
- Uses the strengths of each AI model (GPT-4 for structure, Claude for tone, Gemini for context)
That’s when the magic happens.
Here’s the version that helped me build the core assets for my first productized service:
Prompt:
“You are a product marketing strategist. I want to create a 3-email welcome sequence for a service that helps startup founders validate SaaS ideas. Break each email into: 1) Hook 2) Core Insight 3) Call to Action. Make it sound like a founder sharing lessons, not a sales rep.”
The result?
A 3-part sequence that got me my first $2K client. Written in 7 minutes.
The Hour That Changed Everything
I didn’t take a course. I sat down for one hour, opened ChatGPT and Claude side by side, and started asking:
- What makes a great prompt?
- How do I break tasks into parts?
- What’s the structure behind the structure?
I started saving and tweaking everything that worked.
Within 60 minutes, I had:
- A folder of 12 prompt templates for landing pages, emails, offers
- A go-to format for each type of deliverable
- A sense of which model handled what best
And then I just… used them. Again and again.
Why I Run All Prompts Through Chatronix
I quickly hit friction switching tabs, testing tone, comparing models. That’s when I moved everything to Chatronix. It’s not just an AI tool – it’s a prompt lab.
Here’s how it changed the game:
- I run one prompt and get results from GPT-4, Claude, Gemini, and Mistral
- I version-test ideas without context switching
- The turbo mode makes it fast enough to do live ideation with clients
Now I don’t guess which model will deliver the best result. I just ask all of them.
Table: My Prompt Workflow Before vs After Chatronix
| Task | Before (Manual) | After (Chatronix Workflow) |
| A/B testing prompts | Copy-paste across tabs | 6-model output in one interface |
| Saving top responses | Manual Google Docs | Click-save to named folder |
| Tone comparison | Guess and revise | Use tone slider + Claude preview |
| Idea generation | Limited to GPT-4 or Claude | Turbo multi-model with prompt reuse |
| Client delivery | Required manual edits | AI detection pass + export-ready |
The difference? I execute faster than any freelancer I know. And it looks like I have a team behind me.
What a $20K Month Looked Like Using Prompts
Let’s be real: no one pays for prompts. They pay for what prompts build.
Once I had my prompt system, I used it to sell:
- Mini brand strategy workshops ($500)
- Email sequence builds ($1,500+)
- Offer and landing page critiques ($750)
- Full productized service setup in Notion ($3,000+)
And I wasn’t guessing. I’d send the client a preview and say:
“This was generated in 4 minutes. Want the full stack?”
They always said yes.
My Favorite Stack for $5K Offers
Here’s the exact sequence I still use:
- Claude Prompt – Brand Voice Discovery
“Ask me 5 questions that uncover the founder’s tone, beliefs, and blind spots. Then summarize into a brand voice profile.” - GPT-4 Prompt – Offer Page Drafting
“Based on this voice and service, write a landing page that includes: hero, objections, FAQ, and a pricing callout section. Keep it founder-first, not corporate.” - Gemini Prompt – Social Proof Discovery
“Help me structure a case study based on this short client win: [Insert message]. Make it feel like a casual story, not a testimonial.”
I run all 3 in Chatronix, tweak in real time, and deliver the full set in Notion.
Total work: 45 minutes.
Average value delivered: $3K+.
How to Build Your Prompt System From Scratch
Here’s a quickstart approach I give new freelancers and marketers:
Step 1:
Pick 3 deliverables you want to sell (emails, pages, audit reports)
Step 2:
Break each into components (subject line, CTA, formatting rules)
Step 3:
Turn each component into a prompt template
Step 4:
Test in 3 models (Claude, GPT, Gemini)
Step 5:
Save the best responses and turn them into swipe files
Bonus tip:
Use Chatronix’s turbo mode to generate all model outputs instantly from one prompt. You’ll never go back to tab-switching.
What Prompt Engineering Is Not
It’s not memorizing syntax. It’s not adding “act like an expert” to every query.
It’s knowing:
- Which model is better at summarizing vs selling
- How to split big tasks into smaller asks
- How to inject examples, formats, and tones into a single command
And most of all, it’s about iteration. I rarely nail a perfect prompt on the first try. But the system makes it easy to test, compare, and refine.
ChatGPT – Cheat Sheet pic.twitter.com/jjojwstZ78
— Book Therapy (@Book_therapy223) July 11, 2025
Final Thoughts: You Don’t Need a Team – You Need a Stack
In 2023, I thought “prompt engineering” was a hype word.
In 2025, I built a $150K business because I practiced it for 60 minutes and documented what worked.
If you:
- Sell anything online
- Do client work
- Run your own brand
- Build startup offers
You’re already doing prompt work. The only question is whether you do it once and repeat, or guess every time.
Get systematic. Start stacking.
And if you’re not testing prompts across multiple models in one place yet, start today with Chatronix. It’s where I test everything before I ship it.
If you enjoyed this post, you’ll love what’s featured on 2A Magazine.
