I followed the script. Studied hard. Got the degree. Built a career. Stability was supposed to follow. For our parents, that formula worked. But by the time our generation came of age, it broke down. We inherited serial recessions, student loan debt, a global pandemic, and now AI-related layoffs. The result is a constant background hum of uncertainty.

My interest in trading on the XRP Ledger grew out of that uncertainty. Not to chase alpha or outsmart the market, but to build a system that enforces the laws most traders learn the hard way—capital preservation, defined risk, knowing when to walk away. The gamble is on myself, in a world where neither the job market nor the financial system offers any guarantees.

From Curiosity to Conviction

The layoff came without ceremony. One meeting, one email, and suddenly my calendar was empty. What followed was the modern job search: submitting applications into silence. Multiple rounds of behavioral screens. Technical interviews. Then nothing, or worse, a rejection email after clearing every hurdle. The process felt less like a meritocracy and more like a humiliation ritual.

Between interviews, I needed something to work on. I started exploring how fear and greed move crypto markets in ways that fundamental analysis couldn't explain. The more I explored, the more I noticed who was doing the talking, and how little of it was backed by anything. Analysts hid behind charts. Influencers sold certainty. Neither offered anything reproducible, just anecdote.

I tried to quantify sentiment. I scraped websites, built pipelines, trained models, and tried to turn social media commentary into a tradeable signal. The inherent noise in social media made extracting anything actionable impractical.

But the failure wasn't wasted. I learned how to build machine learning pipelines: data ingestion, feature engineering, model training, evaluation. I had everything I needed, but I was pointing it at the wrong problem.

The conviction came when I stopped chasing sentiment and looked at what was already there: the price itself. Patterns in price, volume, and volatility. Structure that machine learning could work with. Not a crystal ball, but a basis for knowing when to act and when to sit out.

I wasn't tinkering between interviews anymore. What started as self-improvement became something with stakes: the possibility that disciplined trading could generate real income, independent of any employer. I'd rather fail on my own terms.

Laws That Don't Bend

The hard part is building a system that survives contact with the market.

The market's adversarial nature isn't a flaw. It's the mechanism. Capital flows toward those who manage risk and away from those who don't.

That means every trade carries adverse selection: if someone is willing to take the other side, I have to ask why. And because markets are non-stationary and models decay, the confidence behind any given signal is always temporary. No trade will ever feel like enough.

Automation doesn't eliminate my biases. It encodes them. That's why I'm building something boring and interpretable: a system that produces short-horizon price forecasts and abstains from trading when it isn't confident enough to act. Most of the time, it will do nothing. I'm not claiming guaranteed profits, a finished system, or a permanent edge. Just the humility to keep iterating.

The XRP Ledger is what makes this viable. Market data is public, settlement takes seconds, and there are no exchange memberships or compliance costs gating entry. That infrastructure makes a one-person operation possible, but a thin order book means the risks are real: wide spreads, sudden liquidity gaps, and price dislocations that no model fully anticipates.

This time, I own the risk.