I'm Stephen Mordue, an AI-native product and technology leader in San Francisco with 15+ years across medical devices, B2B / B2C apps, and consumer electronics. I build AI applications that ship and move margins, and I'd like to do that as your Head of Software Product / AI Applications.
Lila is building an agentic software platform that lets AI agents conduct, analyze, and iterate on materials, chemistry, and biology experiments, joining software, ML, and wet-lab teams in a continuous loop. [1]
One interface where scientists see what the agent proposed, what ran, what failed, and why, with one-click human override, which is critical for trust in autonomous labs.
Structured capture of instrument and wet-lab results so every run becomes clean training and eval data, based on my microfluidics and medical-device QMS background.
Packaged APIs and workspaces so pharma and materials partners can run scoped campaigns on the platform, with usage-based pricing tied to experiment success.
Also: early team at AliveCor (FDA 510(k) files, HIPAA), Stryker Endoscopy, Abbott Diabetes Care, and Micronics; VP of Product at Kenzen; 6 patents; B.S. Mechanical Engineering, University of Washington. I work AI-native every day in Cursor, Claude Code, ChatGPT, Copilot, and Grok.
Meet the leaders who own the outcomes, inventory live AI efforts and data, and agree on 3 measurable target metrics. Ship one working prototype against a real workflow.
Take the top use case to a production pilot with evals, guardrails, and a baseline. Publish a prioritized AI roadmap with build, buy, or partner calls for each capability.
Turn the pilot into a paved road other teams can reuse, report results in dollars and hours, and line up the next two bets with owners and dates.
If this is useful for the Head of Software Product search or a related AI leadership need, I'd welcome 20 minutes.