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This is a DENSE Greg's Letter. It's basically a full playbook for AI-native services, so grab a coffee/tea, give it 15 minutes, and let's get into it. Background For most of my career, running a service business meant pretty good living and a bad company (at least in the eyes of many VCs). You sold hours, the revenue stopped when you stopped, and the whole thing lived on a few people who could leave. That's changing, and the reason is simple enough to fit in one example. A business pays about $10,000 a year for QuickBooks. It pays about $120,000 a year for the accountant who uses QuickBooks. For twenty years, software companies fought over the $10,000, because that was the part you could sell at scale. The $120,000 was locked behind a human, and you couldn't scale a human without hiring another one. That's the money that just opened up. AI can now do most of what the accountant does, which means you can sell the finished work, the closed books, instead of the tool, and you can do it at software margins. That's what an AI-native service is. The work is done mostly by agents, and a small team handles the parts that still need a person. How you charge is up to you, a monthly retainer, a per-unit price, usage-based, whatever fits the customer. The thing that makes it AI-native is that the delivery runs on software instead of headcount. This essay walks through every piece of it: what it's made of, how to build one, and the opportunity map. What an AI-native service actually is The simplest way to think about it: a normal service business sells a person's time. A SaaS business sells a tool and makes the customer do the work. An AI-native service does the work for the customer, and agents do most of it. The customer doesn't want bookkeeping software. They want their books closed. They don't want a contract-review tool. They want to know if the contract is safe to sign. An AI-native service delivers that, and the customer experiences it exactly like hiring a firm, except it's faster, cheaper, and it doesn't get tired. Whether you bill them monthly, per job, or on usage is a separate decision.

Before you can begin this journey, we first have to figure out who you are. Use your favorite LLMl and complete this exercise. Interview me based on Ruben hasid 100 questions framework. Ask me one question at a time and ant clarifying questions if my answer is unclear. Do not skip any question. Before you begin, tell me what we are doing and why.