
Designing an AI-Powered Clause Library
Zero-to-one AI-driven feature set for a legal technology SaaS startup.

Bringing user insights into product strategy since the '00s.
Organizations that move fast and pivot successfully aren't guessing. They have someone turning user evidence into insights that enable decision-making in uncertain conditions. I'm that person.
Research that sits in a slide deck doesn't help anyone. The value of user research is measured in decisions made better and faster, risks identified before they become expensive, and product directions validated before engineering commits.
Here's what changes when a senior researcher is embedded in your organization:
Research becomes a capability, not a cost center. Instead of commissioning one-off studies, you get a system: recurring insights wired into your decision-making cadence, stakeholder relationships that sustain themselves, and a research practice that compounds over time.
Case studies from recent product research and strategy work.

Zero-to-one AI-driven feature set for a legal technology SaaS startup.
Mixed-methods product-market fit research.
Accessibility evaluation and program-building.
Rapid discovery and design for a mobile-first predictive analytics application at one of the world's largest copper mines.
Generative field ethnography to identify personas and unmet needs for a next-generation navigation experience.
I work at three levels in parallel:
My methods span the full research spectrum: discovery and design sprints, contextual inquiry, in-depth interviews, jobs-to-be-done analysis, journey mapping and service blueprinting, persona definition, usability testing, survey research, and behavioral analytics. I pick the method that fits the question, not the other way around.
I've worked across healthcare, fintech, legal tech, insurance, telecommunications, procurement, and enterprise SaaS. The domain matters less than the complexity. I do my best work in products where the problem space is tangled, the stakeholders are many, and the path from evidence to action requires translation across teams.
I used AI to help me create the content on this site. Did I write every word? No. Did I review, brainstorm, and iterate on the content with some AIs? Of course. Why wouldn't I? Web copy has a distinct rhythm and tone. It's punchy and effortlessly authoritative. That's not how I write. Or think. So of course I used AI for some of the site copy.
Our oldest kid tells me that I should've written all this myself without relying on the clankers. I get it. But I also like to work fast and ship. So I jammed on the content with Opus 4.6, had it build an easily-maintainable site, and stood up v1 within about 24 hours from the first prompt. It's a tool. One I found helpful.
Again, I get it. I understand that current AI offerings are just uncomprehending stochastic parrots that we grant a sometimes-concerning amount of agency. And data centers are the next socio-ecological disaster-in-progress. I feel like I'm making typical Gen-X excuses here, and maybe I am. But what am I gonna do? Not use AI? In this economy? You first. ;-)
I wrote that disclosure. And this sentence. And now I'm trying to avoid an infinite loop.
I'm currently exploring principal, staff, and director-level research roles at companies building complex products. Open to longer-term strategic consulting roles as well. Reach out if your team is working on wicked problems where rapid and valid research needs to be wired into how you make decisions.