introducing land ops
an ai-operated land acquisition pipeline — what it is, why i built it, and what's next.
land ops is the first project in this portfolio to reach production. it's an ai-operated land acquisition pipeline that processes thousands of leads, qualifies them against market data, generates personalized outreach, and manages deals through to closing.
the thesis is simple: land investing has strong unit economics, but the operations don't scale with a solo operator. finding leads, qualifying them, reaching sellers, managing responses — it's high-volume repetitive work that compounds when done consistently and collapses when it doesn't.
land ops removes the bottleneck. the system handles lead processing, qualification, outreach timing, and follow-up sequences. the operator focuses on deal decisions and relationship management — the parts that actually require judgment.
the architecture is a monorepo with four applications: an operator dashboard, an api backend with job queues, a public-facing acquisition site, and a va calling console. the entire system is validated by a comprehensive suite of holdout scenarios that run on every deployment. zero failures is the ship gate.
what makes this different from "crm with ai bolted on" is the world model. the system maintains structured beliefs about markets, sellers, and pricing that evolve based on observed outcomes. it doesn't just execute rules — it learns what works.
current state: production deployment live, all go-live items complete, pre-launch in progress.
read the full breakdown on the land ops showcase page.