I work on the gap between what is known and what gets acted on.
I co-founded ResiDesk. We help multifamily operators hear what residents are actually telling them, and act on it before small issues turn into expensive ones.
Before that I worked at Climb Credit and BlackRock. Before that I studied applied physics at Cornell and started writing code in a lab because it was the fastest way to fix a slow process.
The thread across all of it is the same: useful information stuck in the wrong place, reaching the wrong person, arriving too late.
AI for operationsResident signalsWorkflow designDecision support
Both of my parents have PhDs, so the assumed path was academic. I studied applied physics at Cornell because it sat between the things I liked most: fundamental science, real systems, and hard problems that still mattered outside a classroom.
Software came in through the side door. I was in an electron microscopy lab and wrote code to make a magnetic-noise setup faster. It saved hours of manual work immediately. That was the first time I felt what software could do when it closes a loop for someone, and it pulled me off the original track.
The industries have changed since then. At BlackRock I worked on making institutional tools usable for advisors. At Climb Credit we underwrote against outcomes, not surface-level safety. At ResiDesk we turn resident conversations into something operators can act on before small problems get expensive.
Cornell
Software was an accident.
I wrote a tool in an electron microscopy lab to speed up magnetic-noise setup. It worked right away, and that was enough to change the plan.
BlackRock
I need the problem to be real.
I came back six months later, re-interviewed, and moved to New York. It was the first place I noticed how much better I work when the problem has real stakes.
Climb Credit
We asked a better question.
Instead of who looks safest on paper, we asked what happens to earnings after the program. That reframed underwriting, product, and data, and took annual loan volume from $1 million to $300 million.
ResiDesk
The signal is already there.
Residents tell operators what matters every day. The work is making those conversations useful before the issue gets expensive.
The work has mostly been the same job in different settings: find where useful information is stuck, and build something that helps a person act on it.
ResiDesk
7%
Higher renewals and rent from listening to what residents were saying and acting on it sooner.
Climb Credit
$1M → $300M
Annual loan growth after shifting underwriting from surface-level risk to actual outcomes.
BlackRock
$40M ARR
Retail analytics product taken from zero to $40 million in recurring revenue in year one.
We help multifamily operators understand what residents are telling them across renewals, rent, maintenance, and staffing. The product works because it gives teams real context earlier, not because it looks impressive in a pitch.
We underwrote against a different question: not who looks safest on paper, but what happens to a graduate's earnings. That changed who got funded, what data we collected, and how the product had to work.
The job was turning institutional infrastructure into something advisors could actually use with clients. Same information underneath, better interface, better decisions.
I write when something everyone seems to agree on does not sit right with me. Most of it circles back to AI, how products actually get adopted, and why the distance between a compelling demo and a reliable tool is longer than people think.
If a tool does not help someone reach a better decision faster, it is furniture.
Understand the job first.
Without knowing what someone is actually trying to do, you are just rearranging pixels.
Buy the car, not the engine.
The model is one part. Context, tools, guardrails, and where it fits in someone's day, that is the rest.
Demos lie by omission.
What matters is whether people still reach for it on a Wednesday afternoon, mid-mess, with no audience.
FAQ
Module 08
Questions I get asked a lot
What kind of AI work do I do?
I build AI that fits into how people already work. At ResiDesk, that means analyzing resident sentiment, building copilots for property teams, and designing agent systems that surface the right context before small problems become big ones.
What have I built before ResiDesk?
I worked at Climb Credit and BlackRock. At Climb, I helped grow annual loan volume from $1 million to $300 million. At BlackRock, I built a retail analytics product that reached $40 million ARR in its first year.
What do I usually write and speak about?
How AI products actually hold up in practice: agent workflows, LLM evaluation, product loops, and what separates a compelling demo from something that works on a Tuesday afternoon. My recent 20for20 talk started with resident conversations across 30,000+ units in 11 states.
What is my view on AI?
I care less about whether something looks impressive and more about whether it helps someone make a better call. That usually means getting context right, measuring what matters, and keeping a human in the loop before automating anything.
I have invested in more than 100 startups and mentored through Techstars. I tend to back founders who are close to the problem, close to the customer, and clear-eyed about what they do not know yet.
That honesty matters more now than ever. Generic advice is everywhere. What still counts is specific context, good judgment, and helping someone get to the next real decision faster.
