Former litigator with a decade of courtroom experience turned backend engineer and LegalTech architect. After 10 years of navigating the unpredictability of the court system, I transitioned into software development to build systems that replace legal intuition with computable data. A pragmatic developer (PHP for business logic, Go for high-load parsing, Python for LLM tooling and experimentation) who builds tools to solve the exact problems I faced in practice. Currently developing Lexometrica.com - a predictive analytics engine that evaluates the success probability of appellate court decisions. Recently published research exposing LLM "sycophancy" in legal analysis, proving that AI models artificially inflate a lawyer's chances of winning when fed biased arguments, and designed a multi-model consensus architecture to neutralize it.