I was fifteen when I first stood in front of a CNC machine at Senai. Not a keyboard. Not a screen. A machine that cut metal down to the tenth of a millimeter, where a wrong input didn't throw an error message, it ruined a piece of material you couldn't get back.
That was 2015. I was training to be a machining technician, but software was already the plan. I'd loved computers for as long as I could remember. Machining was something else: an opportunity that showed up, and I've never been able to say no to a chance to learn something new, even when it had nothing to do with where I thought I was headed.
The machine that taught me to think in systems
There's something about machining that doesn't get talked about enough when people discuss "unconventional paths into tech": it teaches you precision as a mindset, not just a skill. Every program you write for a CNC machine is, in a very literal sense, a sequence of instructions executed by a machine. Tolerances. Order of operations. What happens if step three runs before step two.
I didn't know it at the time, but I was already thinking like a programmer. I just didn't have the vocabulary for it yet.
In 2016, while still finishing my technical training in Mechanical Engineering, I started a second technical degree, this time in Information Technology, at Colégio Técnico Industrial. Two tracks, running in parallel. Machines on one side, code on the other. I wasn't choosing between them yet. I was just curious about both.
The competition that made the plan real
The confirmation wasn't a decision I made quietly at home. It was public, and it had a scoreboard.
In 2017, I competed in Web Design and Development at Senai's "Olimpíada do Conhecimento," a competition that brings together the best students from every Senai unit in their field. I won bronze.
Honestly, the hardest part wasn't the code itself. It was proving, in real time, on a stage, under a clock, that the thing I already knew I wanted was actually within reach.
That medal didn't hand me a career. What it gave me was proof, to myself first, that I could compete at this, and hold my own.
Learning software the way I'd learned machining
By 2018 I was working at Code49 as a development intern, refactoring front-end interfaces in Angular for property management systems. Later that year I co-founded Gugale, and for the next three years I was building production systems across completely different industries: an HR evaluation platform, a legal lead-management tool that automated document processing from the São Paulo Court of Justice, deployment pipelines for a distribution company. Different domains, same underlying instinct from the machine shop: understand the constraints of the system before you touch anything, then build something that holds up under real conditions.
In 2021, I joined Robin, a recruitment tech company based in Utrecht, as a Software Developer. I've been there since, and my role has grown from writing code to leading technical decisions end to end, from architecture calls to shipping features that move the business forward.
Why I'm circling back to AI now
Here's the part that closes the loop for me. Later this year, I'm starting a postgraduate degree in Applied AI Engineering. Not because I'm chasing a trend, but because the same question that pulled me out of the machine shop is pulling me here again: how do systems actually work, and how far can I push them.
I already built an internal AI assistant at Robin that classifies support tickets and retrieves context from past resolved issues, cutting the number of non-bug tickets reaching engineering by roughly 70%. That project made it clear this isn't a side interest anymore. It's the next machine I want to understand from the inside out.
What I'd tell someone starting where I started
If your path into tech didn't start with a computer science degree, you're not behind. You're carrying a different kind of pattern recognition, and at some point it becomes an asset instead of something to explain away in interviews.
Mine started with a lathe and a tolerance of a tenth of a millimeter. Yours might have started somewhere else entirely. That's fine. The machine changes. The way you learn to respect it doesn't.
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