From LLM Noob to custom GPT Pro: What I Learned Building My Own AI Productivity Assistant

If you’d asked me a year ago whether I’d be building my own AI assistant, I’d have probably laughed. Fast forward to today, and not only have I built one I use it almost every day to brainstorm ideas, navigate challenges, and keep my productivity humming.

Let’s rewind a bit. My curiosity was the real driving force behind this journey. I’ve always been the kind of person who wants to understand how things tick and AI is no exception. Watching tools like GPT and Copilot reshape the way we write code, communicate, and even think about work itself made me realize something big: our work environment is about to change dramatically over the upcoming years. Like, “hold onto your hats” level of change.

So I did what any curious (and maybe a little bit stubborn) technologist would do, I decided to dive in headfirst and build a custom GPT tailored to my workflow.

The good news is it was easier than I expected. Setting up a custom GPT is surprisingly user-friendly, even for someone who’s definitely very smart but admittedly not a machine learning expert, yet.

But here’s the catch getting it to behave exactly the way you want takes iteration. I learned pretty quickly that it’s one thing to get a custom GPT up and running, and another thing entirely to make sure it respects boundaries like “don’t give legal advice” or “stay in its lane when brainstorming.” Testing and refining its responses is key and yes, that meant a lot of poking, prodding, and adjusting.

Now, here’s where it gets interesting. I’ve used my custom GPTs for so many things that I’ve genuinely lost count. Need help brainstorming blog ideas? Check. Want a second opinion on navigating a tricky team dynamic? Check. What an idea for enhancing team engagement? Check. Sometimes it even feels like it’s reading my mind (which is both cool and a little unsettling).

One thing I learned is that GPTs feel more robust and helpful than Copilot — at least in my experience. We use Copilot in the office, but it’s not nearly as powerful (or as collaborative) as my custom GPT. Maybe it’s because of company-imposed security limitations or the way it’s integrated, but for me, GPTs just feel like a better fit.

Of course, I’d be lying if I said it’s all sunshine and roses. The one big watch-out? Don’t get lazy. AI is powerful, but it’s still your responsibility to review what it produces. Trust, but verify.

Building my own GPT has made me more productive, more creative, and, dare I say, more future-proof. If you’re even a little curious about AI, I’d say: dive in. It’s easier than you think — and the rewards are worth it.

Ai Generated image of Maryanne thinking