Not Just Vibes: Why I’m Building a Real Prompt Engineering Portfolio
“The moment I realized I was already doing the job I wanted, I knew I had to start documenting it.”
✨ Why This Post Exists
Today I sat down to work on a prompt engineering course… and ended up learning way more than I expected — not just from the course, but from asking better questions (to ChatGPT, no less).
What started as “What’s a GitHub repo?” spiraled into a deeper understanding of what prompt engineers actually do, how Python fits into the picture, and why I should be showing off the work I’m already doing.
So this post is both a journal and a reminder:
🧠 I’m not “going to be” a prompt engineer. I already am one.
🧰 The Stack I’m Working With Right Now
Here’s a quick look at the tech I used today and what I learned about each:
Make + Zapier: For automating data flows between tools (e.g., Zoom → transcript → OpenAI → Google Sheets → Go High Level).
OpenAI’s API: To turn call transcripts into actionable summaries.
Go High Level (GHL): My website lives here, and I’m integrating workflows directly into the site now.
GitHub Repos: A digital treasure chest for code, documentation, and collaboration (also: I finally understand what these are now).
Python: Not required, but wildly useful for wrapping prompts into scripts, automating logic, and scaling past no-code tool limits.
🔗 What Is Prompt Chaining, Anyway?
I learned that prompt chaining means linking prompts and outputs together in logical flows.
Think: Prompt 1 creates an idea → Prompt 2 expands it → Prompt 3 translates it → Prompt 4 generates a final response.
It’s more than writing “good prompts.” It’s about designing systems of thought — like setting up an assembly line where AI is the entire factory.
⚙️ Why Code Still Matters
Sure, tools like Make and Zapier are amazing. But today I had a lightbulb moment:
✨ Python isn’t replacing tools — it’s unlocking superpowers.
If I ever want:
Condition-based flows
Retry logic
Logging
Parsing complex outputs
Deploying AI into software
…I’ll need some Python. And that’s OK. I’m learning. (One if/else statement at a time.)
📸 Portfolio, But Make It Real
Instead of just tweeting “#buildinpublic,” I realized it’s time to document the actual stuff I’ve built.
You can see my first walkthrough post here:
👉 Turn Zoom Transcripts Into Actionable Tasks
And this blog? It’s the beginning of a whole new habit.
💡 What I Learned Today
I’m already doing the kind of work companies hire “Prompt Engineers” to do.
Python isn’t scary — it’s just detailed.
Prompt chaining is a logic puzzle, and I love those.
Blogging makes everything feel more real and less like I'm shouting into the void.
🔜 What’s Next?
Coming soon:
More case studies of real builds
More blog posts like this one
A YouTube channel, maybe (still scary, still thinking about it)
🍷 Final Thought
I’m not just prompting. I’m building.
And every time I write it down, I move one step closer to the life I want — where curiosity, creativity, and code come together to make something useful (and a little magical).
