Physics PhD in Quantum Chaos. Ex-Citadel Engineering. Writing & building at the edge of LLMs, data platforms, and indie software.
“First-principles from physics, gut-feel from years of debugging hundreds of billions of records.”
My work spans applying LLMs to improve data/ML pipeline reliability, using first-principles physics to plan petrochemical plant construction, developing hedging strategies for insurance products at a publicly traded company, and debugging data-quality issues inside hundreds of billions of records at a hedge fund.
Currently focused on orchestrating AI agents to build a production SaaS platform, and writing about what works when the tools change every three months.
If mental math is not about talent or random tricks, then the training question becomes simpler: train facts, patterns, estimation, and calm repetition.
People who are good at mental math are usually not doing the same arithmetic. They are doing easier arithmetic, because they see how to simplify the problem.
Most mental math advice treats arithmetic like stage magic: memorize a few tricks, think faster, impress your friends. That misses the point.
Open to new collaborations, conversations about data systems, LLM infrastructure, or the kind of side projects that turn into real businesses. Reach out — I reply.