Building AI Products In The Probabilistic Era

"I was recently trying to convince a friend of mine that ChatGPT hasn't memorized every possible medical record, and that when she was passing her blood work results the model was doing pattern matching in ways that even OpenAI couldn't really foresee. She couldn't believe me, and I totally understand why. It's hard to accept that we invented a technology that we don't fully comprehend, and that exhibits behaviors that we didn't explicitly expect."

"When we started building businesses on the Internet three decades ago, the skepticism was similar. Sending checks to strangers and giving away services for free felt absurd. But those who grasped a new reality made of zero marginal costs and infinitely scalable distribution became incredibly wealthy. They understood that the old assumptions baked into their worldview no longer applied, and acted on it."

"Many of those playbooks have become obsolete. Something fundamental has shifted. General purpose artificial intelligence has created a rupture in the fabric of the tech industry, upending how we design, engineer, build, and grow software - and thus businesses that have software at their core. We're now in a liminal moment, where our tools have outpaced our frameworks for understanding them. This is a technical, epistemological, and organizational change"

AI's pattern-matching capabilities can produce surprising behaviors that exceed creators' expectations, challenging assumptions about model knowledge and privacy. Observers often dismiss rapid AI progress because it conflicts with existing mental models. Historical technological shifts, such as the Internet's commercial rise, similarly disrupted intuition and economic logic, rewarding those who adopted new realities like zero marginal cost distribution. Established product and growth playbooks have become partially obsolete as general-purpose AI alters how software is designed, engineered, built, and scaled. Organizations now face a liminal moment in which technical capabilities outpace conceptual frameworks, requiring new epistemological and organizational approaches to leverage AI effectively.

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