An AI-Native Attorney and software developer empowering your legal department with AI agents, advanced prompting, and automated workflows—all backed by the protection of a licensed law firm. I want to be a Legal Quant because I view the law as a computable framework rather than static text. Throughout my career, I have consistently sought to bridge the gap between complex legal architecture and automated technological execution. Whether writing Python scripts to parse evidence or deploying AI agents to redline MSAs, my fundamental drive is to optimize, scale, and quantify legal risk and operations. I am drawn to LegalQuants.com because it represents the ultimate alignment of my dual competencies: treating legal data as an engineering problem to be solved with code, quantitative analysis, and rigorous systemic design. I don't just review AI product's terms of service; I understand how the foundation models, interact with the underlying hardware. In 2011, I engineered a patch for the Linux kernel optimizing fsync and fdatasync system calls in fs/sync.c for laptop mode. This systems-level expertise allows me to audit highly complex AI infrastructures from the bare metal up. Designing, developing, and improving legal tech solutions and OSS forensics software for European and US law. This includes writing analysis software in Python and architecting secure Docker containers to evaluate technical risks at the code level. Built and led a global team of legal and infosec professionals, enabling enterprise sales to Fortune 500 customers and supporting hyper-growth from a team of ~20 to ~1,000 in 3 years. My Tech Background: (2000): Started programming and switched to Linux fully (2008): Started contributing to the Linux kernel and other open source software projects such as KDE and darkstat, eventually getting a self-written patch accepted by Linus Torvalds (2011 - 2013): Acted as a Regular Contributor for the Institute for Legal Questions on Free and Open Source Software (FOSS), analyzing IP in software (2012 - 2013): Served as a Legal Consultant for ContributorAgreements.org (2013): Researched and contributed to a comparative analysis on drafting options for FOSS contributor agreements (2014): Received an Open Source award for a thesis on copyright issues with contributor license agreements (2015 - 2020): Founded Devidence UG, personally writing web evidence collection and forensics software in Python, and architecting secure, flexible Docker containers Check out my Linkedin for details about my work, publications, and more. Check out Github for patches and more tech-related topics.