Expert Systems, Agent Risk & the Fixer Economy

Co-founder, MakeBell. Engineer-turned-lawyer at the intersection of AI, IP, and digital evidence. Long before AI became a boardroom imperative, Ron was asking: what happens when law governs technologies it doesn't fully understand? With a mechanical engineering background, multiple postgraduate law degrees, and experience as a computer forensics examiner, systems engineer, and co-inventor on patents in EdTech, AI, and IP tokenization. Former roles at IBM, Hewlett-Packard, Wang Laboratories, and Federal Express. Advisor to WIPO Green. Visiting Fellow and lecturer at City University of HK School of Law and CUHK.

About This Episode

Ronald's tech career predates AI being a boardroom imperative by decades — IBM (on the same GM manufacturing team as pre-Craigslist Craig Newmark), Wang Labs, HP, FedEx Singapore (where the client-server system later used for Apple/Foxconn supply chain was first architected), then computer forensics, then law. He co-founded MakeBell with Kenneth, teaches AI Law at CityU and CUHK, and is building ARA-eVals — an open-source agent risk assessment project. We dig into the symbolic-to-generative-to-neurosymbolic arc, why vibe-coded agents will break at enterprise scale (and the coming "fixer economy" for cleanup specialists), and one oral-exam trick for assessing students in the GPT era.