At Mindsprint I made changes to servers in several countries, in the cloud and on premises. A mistake there never stayed where it happened. Something changed in one place could wake up a team three time zones away.

So I built a habit, and it is still the first thing I do. Before touching anything, I ask three questions: what could break, what would it take down with it, and what would catch it? On our global virtual desktop migration, that meant building rollback pools before the first desktop pool moved, so nobody would lose access if the new setup failed.

I bring the same reflex to markets. When I look at a trading idea, my first question is not how much it could make. It is how it fails, and what I will do when it does.

I started investing in 2021, with no finance degree and no trading desk behind me, and treated the account as a laboratory rather than a bet. Real money taught me position sizing, options pricing and drawdown discipline in a way no simulator could, because every loss was real.

It also showed me the weakest component in the whole process: my own judgement. I stay sharp under pressure. In quiet markets, I take trades I shouldn't, and trying harder did not change that.

So I stopped trying to train the flaw away and started designing around it. I'm building a system that takes my discretion out of execution and makes every rule pass a test on historical data before any money follows it. Every trade starts with a stop-loss and a risk-reward ratio set in advance, and I try to be honest about the difference between a good decision and a lucky result.

My computer science degree gave me the tools to build models. It gave me nothing to judge whether a model makes economic sense.

I can tune a strategy until its equity curve looks beautiful and still not know what risk it is carrying. A backtest shows what would have worked in the past. It cannot say why, or whether the reason will still hold. I have learned that from failed backtests and broken assumptions, more than from the ones that passed.

That gap, between a curve that looks good and an understanding of what drives it, is the one I most want to close. A model should rest on economics, not just on history: on valuation, on derivatives, and on how interest rates and central banks move prices.

I played competitive chess from 2013 to 2017 and reached a FIDE rating of 1548. I still play online.

The habit it left me with is simple. Before I fall in love with my own move, I look for my opponent's strongest answer to it. Chess also taught me to judge the position actually in front of me, not the one I hoped to reach.

I apply the same check to trades. Before I put money behind an idea, I try to find the best case against it: what does the other side of the trade see that I don't?

In 2024 I spent the last semester of my degree at CY Tech in Cergy, near Paris, as one of five students chosen from my batch. I finished my final-year project there and took courses on French institutions, French identity and cross-cultural practice.

I have travelled to thirteen countries, but living in one is different. When a trip gets unfamiliar, you go home. When you live there, you can't, so you adjust.

It taught me to ask questions early, to be comfortable as the least experienced person in the room, and to stop treating my own way of doing things as the default. I would rather be corrected early than be wrong quietly. I kept learning French after I came back, and I'm working toward B1.

Being careful has a side effect: I tend to explain how something works before saying why it matters. My early updates at work were full of technical detail. The people making decisions needed to know what the work meant for the business, not how a policy replicates between servers.

Learning to lead with the consequence instead of the mechanism has been harder than any certification. I still catch myself explaining before concluding. When I do, I stop, and start again with the point.