I'm a software engineer in the middle of a transition — from cloud and distributed-systems architecture into AI Engineering — and I decided to do it in the open.

Most "how to become an AI Engineer" content is one of two things: PhD-in-ML gatekeeping, or hype threads. Neither helped me. So I'm writing the thing I wish I'd found: the real transition, with the trade-offs made explicit and the code open for you to take.

And this space is more than a blog: it's the workspace where I run that transition in the open — building AI agents, sharing the artifacts as I make them, and collaborating on open source as I go. I'm not here as an authority; there's no master of AI yet — the field is too young. I write as a peer, learning alongside you, experimenting out loud and showing what works and what doesn't.

What I'm not going to do

I won't claim years of agentic experience I don't have — the tech is new, my hands-on AI work is months old, and I'll say so. I won't sell you a shortcut. The substance I bring isn't the AI hype; it's ~two decades of SDLC and distributed systems — the unglamorous production rigor (evaluation, observability, architecture, cost, failure modes) that most AI work skips. AI is the newest layer on that, not a fresh start.

The commitment

• Honest over impressive. Real trade-offs, including what didn't work. If I don't know something, I'll say so. A pitch that can't survive a hard question isn't worth writing.
• Show the machine, not just the output. Everything here is public and reproducible — the code is the argument.
• Reader-first. The goal is to help you build better. Whether it helps my own repositioning is a by-product, not the point.
• Sustainable, not performative. I have a full-time job. This grows on weekends, at a pace that survives a bad week — a cadence that lasts beats a burst that burns out.

If you're on the same path

Your background isn't a deficit to overcome. It's the thing that makes you rare in this lane. Build in public, ship small, and let the artifacts do the arguing — and if any of this is useful, take it, improve it, and build on it in the open.

That's the deal. Let's build.