Hear what happened
Start with the resident's own words. Scores and categories can wait.
Building ResiDesk
Most of my time goes into ResiDesk. We help property teams answer residents, keep the history straight, and notice when the same problem is happening across a building or portfolio.
Before ResiDesk, I built advisor software at BlackRock and ran product and engineering at Climb Credit. In both places, the useful work started by sitting with the people doing the job, measuring what changed, and fixing what fell apart on a normal Tuesday.
ResiDesk
Property teams hear from residents all day, in texts, reviews, tickets, surveys, calls, and renewal notes. The hard part is keeping the history together, finding the right policy, and getting the next step to someone who can help.
We started ResiDesk because that work was scattered across too many places. I spend most of my time on the data and product, plus customers, sales, hiring, and whatever else the company needs that day.
Visit ResiDeskStart with the resident's own words. Scores and categories can wait.
Add the lease, policy, unit, earlier messages, and what the team has already tried.
Answer, repair, escalate, explain, or change the policy. Give the decision an owner.
When the same problem keeps coming back, make it visible to the people who can fix it.
How I got here
I grew up around research and studied applied physics at Cornell. Software became real to me in an electron microscopy lab. A small tool I wrote saved hours on a magnetic-noise experiment. That was when software stopped feeling like coursework and became a way to help.
It taught me a standard I still use. Did the work get easier?
At BlackRock, I worked across product and engineering on advisor tools. A prototype could win the room and still lose to the spreadsheet people trusted the next morning.
As CTO and CPO, I helped bring graduate earnings into Climb's product, data, and underwriting instead of treating a borrower's credit score as the entire story.
At ResiDesk, I listen to the conversation, follow the work it creates, and look for the problems that keep coming back.
One ResiDesk program reported this lift after a property team acted on resident feedback sooner. Law360
Climb Credit's annual loan volume grew across this range while outcomes moved into the product. TechCrunch
I helped take an advisor analytics product from zero to this run rate in my first year at BlackRock.
How I work
Until you know that, the model debate is usually a distraction.
I believe the pain. Then I want to know what happened, why it happened, and what we can change.
I care about what happens when the queue is full, the edge case is real, and nobody is around to rescue it.
Writing and talks
I write when an idea still feels fuzzy. The test is simple: did this help someone do the work, or did it just make the demo easier to sell?
Read the SubstackTalks and conversations
3 videosWriting, interviews, and events
9 piecesWhy context, checks, handoff, and the rest of the system matter more as models get closer together.
2026 AI from the owner and operator seatA BuiltWorlds conversation about where AI changes underwriting and operations, and where it does not.
2026 Resident sentiment: presentation and podcastA conversation about what residents say, what operators can learn from it, and what should happen next.
2025 What Wi-Fi complaints tell ownersA white paper built from the complaints residents actually make about Wi-Fi.
2025 NOI, Not NoiseWhy resident conversations should reach the operating decisions someone already has to make.
2024 ResiDesk in Law360How we connect resident conversations to retention and the decisions property teams already make.
2024 Applied AI in real estateA longer interview about putting AI inside property-management work instead of around it.
2024 Practical AIA profile spanning real estate, finance, and education, with the focus on where AI is actually useful.
2016 Climb Credit in TechCrunchThe early bet behind Climb: build education lending around whether a program helps someone earn more.
Contact
I like talking with people working on housing operations, AI that has to survive real users, product decisions, and the ordinary mess of building a company.
A useful note usually has a customer problem, some context, and a decision you are trying to make.
I am less helpful with a broad AI inspiration call when there is no specific work attached.