I wasn’t always sold on AI.
Sure, I followed the headlines. I tried out the early tools. But for a while, it all felt like hype layered on top of buzzwords, with a dash of magic. Cool demos, yes — but not something I could rely on in the trenches.
Fast forward to now… and I’m having full-blown conversations with ChatGPT about project logic, system design, even emotional intelligence frameworks. Somewhere along the way, it clicked. Not all at once — but slowly, use case by use case, AI stopped being a toy and started becoming a partner.
Here’s how that shift happened — and how I’m using AI differently these days.
It started as a helper… now it’s my second brain
In the beginning, AI was the occasional assistant. A faster way to draft emails, rewrite something, or answer a quick question when I was too lazy to Google.
But then I started feeding it real context — architecture decisions, risks I needed to assess, emotional tone I wanted to convey. And to my surprise, it wasn’t just regurgitating answers. It started giving me perspective.
Now I use AI to:
- Debug ideas before I even write code.
- Simulate dialogues between agents for emotional intelligence models.
- Build out RAG pipelines with Elasticsearch and see where retrieval fails.
- Rapidly test prompts for clients before anything goes live.
- Generate rationale behind ESG goals in a platform I’m building.
It’s not perfect — but neither am I. Together, we move fast and break the right things.
Skepticism taught me to design better prompts
One of the reasons I didn’t buy into the AI hype early on is because most outputs were surface-level. Generic. Boring.
Then I realized the problem wasn’t the model — it was me. Or more specifically, the way I was talking to it.
Once I started treating AI like a junior dev with huge potential — someone who needed context, structure, and purpose — everything changed.
Now my prompts look like mini design docs. I share what I’m building, how I’m thinking, and what I want in return. And the results? They’ve gone from “meh” to “wait, that’s actually useful.”
Where AI is saving me time (and where it’s not)
🕐 Saves me time:
- Writing rationale for AI-generated decisions (like ESG goals)
- Analyzing large texts or logs I don’t have time to sift through
- Brainstorming edge-case scenarios during risk assessments
- Creating first drafts of game economy balancing tables
- Playing devil’s advocate on architectural decisions
🐢 Still takes time (and trust):
- Fine-tuning emotional tone for real conversations
- Building actual production systems — prompts help, code still needs work
- Explaining business logic in a way that doesn’t oversimplify
So no, AI hasn’t replaced me. It just made my brain more scalable.
Using AI has made me think differently
Funny enough, the more I use AI, the more human my thinking has become.
It’s forced me to clarify my assumptions, explain things clearly, and break down big problems into smaller chunks — because that’s what AI needs to give good output. And that same clarity? It helps me communicate with actual humans better, too.
Which is weird. But also kind of amazing.
So what’s next?
I’m not chasing the next hot tool. I’m more interested in how AI fits into the way I already work — how it helps me think, build, communicate, and improve. Whether I’m designing risk systems, experimenting with AI twins, or building game loops, AI is part of the workflow now.
And if you’re still skeptical? I get it. But try giving it a real problem. Explain it like you would to a smart friend who just needs context.
You might be surprised what it gives back.