Hear what happened
Start with the resident's own words. The score can come later.
Co-founder, ResiDesk
Most of my time goes into ResiDesk. We help property teams answer residents, see what keeps going wrong, and get each issue to someone who can actually do something about it.
Before ResiDesk, I built advisor software at BlackRock, then ran product and engineering at Climb Credit. The industries changed. The habit did not: stay close to the customer, measure what changed, and keep going until the thing works on a normal Tuesday.
ResiDesk
Residents tell a building what is broken every day. Those messages show up in texts, reviews, tickets, surveys, calls, and renewal notes. Another inbox is rarely the answer. The team needs the history, the right policy, and a clear owner for what happens next.
We started ResiDesk to make that work easier. I spend most of my time on data and product, and the rest on customers, sales, hiring, and whatever else the company needs that day.
Visit ResiDeskStart with the resident's own words. The score can come later.
Bring in the lease, policy, unit, prior messages, and what the team has already tried.
Answer, repair, escalate, explain, or change the policy. The decision still needs an owner.
When the same problem keeps coming back, make sure the people who can fix it see the pattern.
How I got here
I grew up around research and studied applied physics at Cornell. Software clicked for 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 started feeling useful.
The first useful program I wrote saved a researcher hours. I still like that standard: 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 someone trusted the next morning.
As CTO and CPO, I helped bring graduate earnings into the product, data, and underwriting instead of treating a borrower's credit score as the whole story.
At ResiDesk, that means listening to messy conversations, following the work they create, and learning from problems that repeat every day.
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, arguing about the model is usually a distraction.
Take the pressure seriously. Separate what happened from what caused it. Then make the next move clear.
I care about what happens when the queue is full, the edge case is real, and there is nobody around to rescue the workflow.
Writing and talks
I usually write because something still feels fuzzy. The test is simple: did this help someone do the work, or did it only 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 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 am most useful when the problem involves housing operations, AI in real work, product judgment, or the practical mess of building a company.
Good reasons to write: you have a customer problem, a messy rollout, or a decision that gets clearer with the right context.
Less useful: a broad AI inspiration call with no customer, no real work, and no next decision.