Product manager.
Builder. Gardener.

I build software that helps people manage the practical parts of life. Currently a PM at AppFolio, where I work on rental applications for property managers. Before that: startup life, data science, and a winding path through ecommerce and small business.

I care about shipping things that actually work, staying close to my family, and building a few quiet tools that might outlast me. Proud future ancestor of the Choctaw Nation of Oklahoma. Probably the most optimistic person you'll meet.

Work

AppFolio

Now

Product Manager, Rental Applications

Rental applications were stuck in a legacy system—forms that couldn't be saved, couldn't be resumed, and didn't meet basic consumer expectations. Every applicant was essentially anonymous, with no way to measure what was working. I rebuilt the experience to be consumer-grade, introduced applicant accounts as the foundation for a network, and created performance metrics so property managers could finally see what was happening with their applications.

Lively

Nov 2019 – Dec 2022

Product Manager ← Data Scientist

Early-stage startup with no visibility into how product decisions affected core metrics. No data science function. No reliable way to explain our data model to financial partners who wanted to integrate with us. I built the APIs and migration flows that moved over $50 million in assets from major financial institutions onto our platform, giving them a compliant HSA offering without building the infrastructure themselves. This work grew into product management as the company scaled.

Oracle

Sep 2017 – Sep 2019

Data Scientist, Applied Research

When you change a model, how do you know it actually made things better? I built a system to run hundreds of evaluations against model updates so we could point to real statistical significance instead of gut feelings. The company was also aggregating location data, browsing behavior, and real-world signals to predict consumer purchases. I had growing concerns about where that data came from and how it was being used—concerns that eventually led me to leave.

Full history on LinkedIn

Tools

How I Work

Translating ambiguity into shipped products

I start with the customer problem, not the org chart. I turn fuzzy inputs into a clear sequence of decisions, small releases, and learning loops so value shows up early. Constraints stay visible, tradeoffs are explicit, and success is defined in outcomes customers can feel and metrics we can measure.

Prompt-as-specification

I use prompts like lightweight specs: goal, context, constraints, and what good looks like. That makes AI outputs more reliable, easier to review, and faster to apply to real customer workflows. The payoff is shorter iteration cycles, clearer decisions, and less time wasted on results nobody can trust.

Rapid analytical validation

I move quickly from question to signal by pairing customer evidence with data. I frame a hypothesis, pull the smallest analysis that can change a decision, and sanity-check it with real-world context. It keeps teams aligned on what matters and helps us ship improvements that actually move the needle.

Technical bilingualism

I work comfortably with engineers and systems details so customer intent survives contact with implementation. I can read code, prototype, and talk tradeoffs early, which reduces rework and speeds time-to-value. The goal is fewer handoffs, cleaner execution, and experiences that feel thoughtful to the people using them.

Elsewhere

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