I advise on strategy and follow through to delivery

The path here

I’ve always been obsessed with how systems do a lot with a little.

That’s what drew me to neuroscience. The human brain runs on 40 watts — the same as a dim light bulb — yet it performs visual search, metacognition, and pattern recognition that we still can’t fully replicate with racks of GPUs. I wanted to know how. What were the heuristics? What was the firing threshold? Why was it so efficient despite being the product of millions of years of messy evolution, not deliberate design? I studied it because I wanted to understand how my own mind worked — why I saw the world the way I did, and what that could teach me about building better systems.

Then I moved into software, because building is thinking for me. If I can see a process that’s wasting time, I want to abstract it out. If a system is bloated, I want to find where the signal is getting lost in the noise. That instinct doesn’t stop at code — it extends to teams, to culture, to the decisions people make when they’re working with incomplete data. And they almost always are.

Operion came from watching the same problems play out inside every enterprise I worked in. The signals were there — burnout building, collaboration breaking down, people making calls based on less than complete information — but no one was acting on them because no one was seeing them clearly. We spend most of our waking hours at work. It should be good. People deserve to feel heard, and leaders deserve to see the real picture before it becomes a crisis.

After three enterprises, seeing the same patterns each time, I knew I could do this better — and that the moment to do it for startups was now, before they calcify into the same problems I’d spent years watching unfold.

“We spend most of our waking hours at work. It should be good.”