Spacecraft don't forgive optimistic math. Neither do marketplaces.
Mars 2020 — the rover in the video above — ran roughly $2B through build and closer to $3B once operations were counted. I owned the mission systems area, about $350M of it, and the scope grew from there. I held the work breakdown structure for Europa alongside it and ran JPL/SpaceX contracts ahead of schedule.
The analysis went up through the program to NASA's head of science. Two awards for exceptional contribution came out of those three years.
Startup time runs about seven to one — the dog years. I wore multiple hats while building a new B2B business, selling into Fortune 500 companies and global banks where a deal meant working five to seven stakeholders. One of five account executives; 75% of company ARR; SaaS up 350% year over year.
I have since spent years on the buying side of that same table, approving vendors for a marketplace rather than selling into one. Watching how a purchase actually gets signed off taught me more about enterprise selling than any deal I closed.
I ran the lending marketplace — the hard money directory and loans page — before Lender Finder existed. Lender advertising revenue went from $420K to $1.26M a year, earned from the audience already there rather than from new traffic.
An entirely new marketplace product, built from the ground up. I scoped the legal, technical, and operational groundwork before a line of it existed, shipped an MVP, then iterated hard — designing the go-to-market, the sales motion, and the partner onboarding as it grew. Eight months after launch it was running at $3M in annual recurring revenue. The build itself gets its own section below.
Investor Concierge started as a test and now runs past $800K a year. I recruited and trained the twelve-person contractor team behind it, across the US and overseas, and built the lead routing and scoring that decides who gets called and when — Claude, the OpenAI API and Zapier doing triage that would otherwise cost more headcount than the line could carry. Two further marketplace verticals launched underneath it, inside an $8M unit.
Every marketplace eventually hits the ceiling of its own audience. Powered By BiggerPockets breaks through it — a partner channel that sources investor demand from across the industry instead of relying on site traffic alone. I scoped it as a staged test, proving the economics on a small footprint before asking anyone to fund the real thing, then scaled it into a channel producing thousands of leads a month.
Seven years of saving, then overland from China to Europe.
The idea landed in 2012, on a flight home from China, when it struck me that I had no real notion of what filled the enormous space between China and Europe. It took seven years of saving and planning to answer that — most of them spent at a desk in Pasadena, daydreaming through Jim Rogers and Paul Theroux between budget cycles. On the 1st of November, 2019, I finally left.
Tokyo first, then Hong Kong, and from there by high-speed rail across China through Wuhan to Xi'an — the most historically astonishing place I have ever stood. On to Urumqi, out where the map stops being familiar to most Americans. Over the border to Almaty, down to Shymkent by Kazakh train, across the Caspian to Baku, landing on Thanksgiving night to a planeload of applause. Then Georgia.
I travelled it the way I'd read about it — through business, macroeconomics, geopolitics and music — and wrote the whole way, mostly from trains.
There are no things, only process.— from the first dispatch, 2019
Anyone can quote a number. These are the machines that made them.
A matching experience connecting real-estate investors to lenders by market and loan product — hard money, DSCR, non-owner-occupied conventional, and conventional-alternative. Lenders pay for the leads they receive.
The part nobody sees is the pricing.
I built the pricing model from scratch in a spreadsheet that is still in use today. It starts with the average property price in a given market and works forward: what a typical loan looks like there, what that loan is worth to the lender writing it, and therefore what a single lead in that market can honestly be priced at. Then it runs the other direction — how many lenders a market can support before the leads spread too thin and everyone churns — to land on the supply each market actually needs. The output isn't a price list. It's the supply and pricing combination that optimizes revenue.
Run it yourself.
8 lenders, 15.0 leads each. Healthy — enough volume for everyone to renew.
Assumes 75% LTV, two points to the lender, a 5% lead-to-close rate, and a floor of eight leads per lender per month before renewals stop. Change the assumptions and the shape holds: revenue is set by leads and price, never by adding lenders.
I came into the Mars program office and inherited a reporting apparatus that had grown by accretion — reports produced largely because they had always been produced. I rebuilt it around one question: which of these actually changes a decision? What survived that test got sharper and faster. What didn't got retired.
Fewer reports, better used. It remains the clearest lesson I've had in the difference between measuring something and managing it.
Rotating through functions gave me an unusual vantage point: I could see how the organization's systems actually connected, rather than how the org chart claimed they did. I built a visualization of that data architecture — where numbers originated, what transformed them along the way, and where they finally surfaced to be decided on — and socialized it across the organization.
Understanding a machine end to end is what makes it possible to fix causes instead of symptoms. Nearly everything I've built since has started with the same exercise.
Interest rates, a drum kit, and a house near the red rocks.
My degree is in business economics, and the thing that caught me was interest rates — I spent college pulling apart how they move and what moves with them. Macro and micro have been a running obsession ever since, and they turn out to be relentlessly practical. Pricing a lending marketplace is really just microeconomics with a deadline: supply, demand, and the cost of money explain more of the business world than most business frameworks manage to.
How I operate, written down so it can be argued with.
I want a new bet to pay itself back in about six months — and then I optimize the next five to twenty years. Short-term thinking is a tax on compounding: it buys a quarter and sells a decade. The discipline is holding both horizons at once. Prove it quickly, then build it to last.
A bad number isn't the problem. It's the output of a machine that produced it. Chase the number and you get a patch that holds until next quarter; trace it to its cause and you get a fix that holds permanently. Almost every recurring problem I've met turned out to be a design flaw wearing a costume.
Before a report, a dashboard, or a recurring meeting is allowed to exist, it has to answer one question: what decision changes because of this? If the honest answer is none, it's theater — and theater is expensive, because it costs attention you can't get back. I've retired more reporting than I've built, and every organization was better for it.
Responsibility without authority produces a team that waits. I hand people the decision rather than the task, and hold them to the outcome rather than the method. It's uncomfortable at first and it is the only thing that scales past the reach of one person.
Before asking anyone to fund the real thing, prove the economics on a footprint small enough to be wrong cheaply. Crawl, then walk, then run. Most of what I've launched began as a test deliberately designed to fail fast if it was going to fail at all — which is what made the eventual commitment easy to defend.