BS.

Product manager.
Builder. Gardener.

I build software that helps people do their jobs. More and more that means software that can do the real work itself, and still fit the way people already think. I spend a lot of time in the data, looking for what customers want but can’t find yet. Currently a PM at AppFolio, doing this 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. I am a proud future ancestor of the Choctaw Nation of Oklahoma, and probably the most optimistic person you'll meet.

Work

AppFolio

Now

Product Manager, Rental Applications

The old rental application was stuck. Applicants couldn't save the form or come back to it. Property managers had no way to see what was working, and every applicant was anonymous. I rebuilt the experience so it feels like a modern app, added accounts so applicants can finish later and we can measure what works, and built reporting so property managers can finally see what's happening with their applications. The result: properties on the new flow fill vacancies 3–5 days faster than offline workflows, and submission rates climbed meaningfully. We're in the early stages on the agentic side at AppFolio — the goal is to bring the same JTBD → OOUX → spec-driven method below to that work.

Brava

Now · Side project

Co-founder — built with my brother

College recruiters rarely see athletes who grow up far from the big metro clubs and showcases, no matter how good they are. My brother and I are building Brava nights and weekends for those players: women's soccer recruiting profiles with coach-verified stats, benchmark rankings, and an AI-assisted production pipeline, so they can chart their own path to college soccer instead of waiting to get discovered. I design and ship it end to end — research, product, brand.

Lively

Nov 2019 – Dec 2022

Data Scientist → Product Manager

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. Those concerns eventually led me to leave.

View one-page résumé Full history on LinkedIn

Tools

Free tools. No accounts. Built to be useful.

Life Strategy Matrix

Live

Pick one area of your life, score it, and see where to invest next. Then print the matrix as a one-page guide.

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Native Plant Finder

Live

Find native plants for your garden based on your location and sun conditions. Support local pollinators while reducing water and maintenance.

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Memorial Pamphlet Creator

Live

Create a simple, dignified pamphlet for a memorial service.

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Service of Life Builder

Live

Build a liturgy for a memorial or celebration of life.

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Memorial Preferences Worksheet

Live

A one-page form to print and fill out by hand — record service wishes on paper, no screen required.

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Decision Assist

Live

Weigh your options with clarity. Score choices against what matters most.

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AbiertoClaw

Open source

A free-by-default personal AI assistant over iMessage or the CLI. Swappable model sources — OpenRouter, OpenCode Zen, bring your own, or fully local — with a complexity router and a daily best-free-model picker.

View on GitHub

How I Work

Three steps for building products that fit how people actually think.

Phase 01 · Deep JTBD

The “why” behind the wallet

I start with the customer's actual pain, not the technology. Property managers don’t want an “AI Property Manager.” They want to stop losing Sunday nights to spreadsheets and just know their portfolio is compliant. I keep asking questions until I can name the exact moment a customer would pay $500 right now to never do that manual reconciliation again. Every decision I make after that points back to that frustration.

Phase 02 · OOUX

Map the system of truth

Before an agent can act, it has to understand. I use Object-Oriented UX to map the things customers care about: Lease, Security Deposit, Compliance Rule. Then I figure out how they connect and what details each one carries. When a Lease expires, what should happen to the Deposit? That logic is the brain of the agent. It lives in the model, not the prompt.

Phase 03 · Spec-Driven Development

Ship the technical contract

I combine the map we've built with a solid PRD to build a specification that contains the job to be done, objects that relate, how they interact, and the hard rules on what good looks like. When the customer's job is compliance, that means checking against a real legal model. No hallucinations allowed. I clarify the ambiguities and review the spec adversarially before any code exists, then do the same with the plan: which APIs to call, which models handle what level of complexity, and what success looks like in the UI. The tasks break it into small pieces of work, each refined and verified against the spec before execution. The agent isn’t guessing how to be helpful. It’s working inside a real model of the customer’s world.

The result: I ship a reliable employee that fits the vacancy customers already had.

Elsewhere

What I'm thinking about outside of work.

Contact

I'm always happy to talk about product, tools, or gardening.

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