Writing on AI, real estate, and real-world assets
Answer-first essays on the questions operators, founders, and journalists actually ask — who is accountable when AI acts, how AI rewrites real estate underwriting, what EV charging really earns on a mountain corridor, and why parking is turning into software. Each piece leads with the answer, then shows the data and the operator reality behind it. These are working drafts drawn from Ross's books and field experience.
Who pays when an AI agent makes a mistake?
The party that deployed the agent pays first — accountability does not transfer to the software. The durable fix is an “agent of record”: a named, insurable human or entity bound to every autonomous action, with a tamper-evident trail of what the agent did and why.
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How does AI change real estate underwriting?
AI moves underwriting from a slow, gut-feel memo to a continuous, evidence-backed decision that can be produced in hours instead of weeks. The constraint is no longer analyst time; it is data quality, and the firms that win are the ones that pay down their Dirty Data Tax first.
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What are the economics of EV charging on the I-70 corridor?
On the I-70 mountain corridor, charging is not the product — dwell time is. The money is made by owning the site and monetizing the 20 to 40 minutes a driver is captive, because energy margin alone rarely repays the cost of mountain-grade power infrastructure.
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Why is parking becoming software?
Parking is becoming software because the asset that earns the money is no longer the asphalt — it is the right to use a space at a moment in time, and that right has to be priced, reserved, enforced, and settled in code. The lot is now an API with a curb attached.
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What is the owner-dependence tax?
The owner-dependence tax is the discount a buyer applies to a business that cannot run without its founder. The more decisions, relationships, and knowledge live only in your head, the riskier the company is to own — so the multiple shrinks, and you pay the tax whether you ever sell or not.
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What is the retirement multiple, and how do you raise it?
The retirement multiple is the number a buyer pays per dollar of your earnings — the figure that turns profit into a sale price. The same earnings can sell for 2× or 6×. You raise it by making earnings recurring, provable, and independent of you.
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How do you underwrite a real estate deal in 24 hours?
You underwrite a deal in 24 hours by treating underwriting as a standing data pipeline, not a one-off research project. The speed comes from paying down your dirty data tax in advance, so deal day is assembling a decision rather than starting an investigation.
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When should a human approve an AI decision?
A human should approve when a decision is consequential, hard to reverse, or low-confidence — the human review rule. Draw the threshold on impact, reversibility, and confidence before you deploy, enforce it in code, and route only the decisions that cross it to a person.
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What is an AI-native (intelligent) building?
An AI-native building is one where software is the operating system of the asset — it senses its own state, decides, and acts on its own data. It is not a normal building with apps bolted on; it is a property where one intelligence layer runs operations.
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