Work in progress.

I'm pivoting back to technology after a career that started in tech investment banking and then late-stage private equity at The Carlyle Group in San Francisco and London. I left Carlyle for an industrial turnaround opportunity, ran that business to ~$240M in top-line revenue, and sold it. I came back to technology because AI changed what one operator can build — and because this is the most consequential technology inflection point of my career.

As a first step, I joined Docusign's two-person Corp Dev team and then proactively pivoted into GTM to help drive the launch of Intelligent Agreement Management — turning contracts into AI-readable, AI-actionable objects.

Outside that role, I've been shipping side projects with Claude Code and Factory AI. negotiate.murrays.org has three frontier models autonomously negotiating and closing a Series B term sheet against sealed playbooks, with reasoning traces and a hash-verified audit trail. tribunal.murrays.org runs frontier-model adversarial deliberation — advocates argue opposing sides, judge panels render verdicts. My day job and my side projects pull on the same question from opposite ends: what does it take for enterprise customers to trust frontier AI with consequential data?

What I bring: an operator who's owned a P&L at scale, a former PE investor who can underwrite a business, a GTM person who has launched and driven new product adoption, and a non-engineer who ships at the agentic-architecture level using SQL, Python, and TypeScript on Vercel, Redis, Supabase, and Snowflake.