Autumn 2026Product, data and AIIssue 01
Product manager, data scientist first. Rental applications and payments at AppFolio, data at Oracle and Lively. Now helping small companies put what’s new to work.
The application nobody could finishRebuilt end to end
Native Plant FinderFree tools your agent can run
Applications and payments at AppFolioData at Oracle and Lively
44% to 70%Applications
submitted
Cover: marigolds and hanging amaranth, engraved for this issue.
Think like a scientist. Grow things that last.
Product manager, data scientist first. Rental applications and payments at AppFolio, data at Oracle and Lively. Now helping small companies put what’s new to work. I build free tools that AI agents can run.
44 to 70%
Source AppFolio. Started rental applications that were submitted, old form against the rebuilt flow.
3.4days
Source AppFolio. Properties on the rebuilt application, against those still on offline workflows.
99.1%
Source AppFolio. Application-fee checkout, with an assumed-success window and a recovery path for failed payments.
$50M+
Source Lively, Nov 2019 to Dec 2022. From major financial institutions, through APIs and migration flows I built.
6tools
Source llms.txt, which lists every tool and how to run it.
Submissions went from 44% to 70%, and vacancies filled 3.4 days faster. Here is what changed.
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 felt like a modern app, added accounts so applicants could finish later and we could measure what worked, and built reporting so property managers could finally see what was happening with their applications.
The result: submission rates went from 44% to 70%1 with a zero change-failure rate,2 and properties on the new flow filled vacancies 3.4 days faster than offline workflows.3
Of every 100 applications started
44 Old form
70 Rebuilt flow
26 more of every 100 started applications were submitted on the rebuilt flow.
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 for those players: women’s soccer recruiting profiles with coach-verified stats, benchmark rankings and an AI-assisted production pipeline. I design and ship it end to end, from the first research call to the brand on the page.
An early-stage startup with no data science function and no reliable way to explain its data model to financial partners. I built the APIs and migration flows that moved over $50 million in assets from major financial institutions onto our platform. The work grew into product management as the company scaled.
When you change a model, how do you know it 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. Concerns about where the data came from eventually led me to leave.
Three steps for building products that fit how people actually think.
“Property managers don’t want an ‘AI Property Manager.’ They want to stop losing Sunday nights to spreadsheets.”
I start with the customer’s real problem, 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 properties are compliant. I keep asking questions until I can name the exact moment someone would pay $500 right now to never do that manual reconciliation again. Every decision after that points back to that one frustration.
Before software can act for someone, it has to understand their world. I map the things customers care about (a Lease, a Security Deposit, a Compliance Rule) and how they connect. When a Lease expires, what should happen to the Deposit? That logic is the heart of the product. It lives in a real model of the world, not in a clever prompt.
I turn that map into a written spec: the job to be done, the pieces involved, how they fit together, and the rules for what “good” means. When the job is compliance, “good” means checking against the real law, with no guessing. I pressure-test the spec before any code exists, then do the same with the plan and the work itself, breaking it into small pieces and checking each one against the spec. The software isn’t improvising how to help. It’s working inside a real model of the customer’s world.
The result is software people can trust with real work, built to fit the way they already think.
Free tools. No accounts. Your AI agent can run them too: each one takes URL parameters and registers WebMCP tools.
Find native plants for your garden based on your location and sun conditions. Support local pollinators while reducing water and maintenance.
Open Native Plant FinderRate eight areas of your life and see which one to invest in next. Then print the matrix as a one-page guide.
Open Life Strategy MatrixWeigh your options with clarity. Score choices against what matters most.
Open Decision AssistCreate a simple, dignified pamphlet for a memorial service.
Open Memorial Pamphlet CreatorBuild a liturgy for a memorial or celebration of life.
Open Service of Life BuilderA one-page form to print and fill out by hand. Record service wishes on paper, no screen required.
Open Memorial Preferences WorksheetA plugin for the Hermes agent that keeps it on today’s best free model, smoke-tested daily with a real tool call, with a local model as the fallback.
AbiertoClaw on GitHubHow to run every tool here: prefilled links, WebMCP, or the data directly.
Read llms.txtWords I’ve put together about life, memory, and paying attention. Some poetry, some prose, some longer stories.
My daughter has my dark circles. The same ones I studied in mirrors as a boy and wished away. On her face I feel only tenderness, and something in me settles: what I carried alone, she won’t.
I used to treat being a good dad as a knowledge problem. I’ve modeled my kids’ genetics down to the allele, the coin flips and the certainties, because the math is the one part I can’t change. So I’m changing everything else: the garden, the food, the sunscreen, the early bedtimes. But kids can’t read protocols. They read faces.
The two most durable things I’ll ever make are asleep down the hall.
Read the essayWhen something new might change how your company runs, call me first. A few clients at a time.