Thirteen months ago, AI felt *concrete*—you asked it something, and it gave you an answer. But what I needed wasn’t just answers—I needed a collaborator. I needed iterative exchanges to refine, fine-tune, and polish. That’s when I started leaning into prompt engineering. I took a few online courses, followed experts, and studied results. And it started to click.
Because of my background—writing full-scale MRDs when I started out as a product manager, crafting UX and comms briefs in marketing, and writing user stories as an Agilist—it came naturally. I knew how to structure information, how to guide a process, and how to shape outcomes. I mixed that gumbo of experience and started creating prompts that gave the AI models the clarity they needed—which accelerated the outputs and gave me the momentum and spark I was looking for.
I didn’t just adapt to AI—I trained it to work like me. This wasn’t about chasing trends. It was about scaling what I already knew how to do, without waiting on resources I didn’t have.
This is part of a larger story. A leadership journey. And one I’m continuing to tell.
Next up: What’s in a Name? Exploring the cultural and strategic roots behind “AI Aunties.”
