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Building AI products in the probabilistic era

AI turns products from deterministic functions into probabilistic systems. That requires expanding old playbooks (SLOs, funnels, siloed finance), and reasoning in terms of trajectories, Minimum Viable Intelligence thresholds, and data as company operating system.

Just as physics underwent a conceptual revolution when we moved past Newton's deterministic universe, and into a strange and counterintuitive place made by wave functions, software too is undergoing its own quantum shift. Since the input space is no longer limited, you can't simply write a few selected tests and follow test-driven development: you'll risk breaking critical features without even being aware of their existence. Having a good system in place to constantly sample the right test cases from real-world past usage is one of the most critical new pieces of work required today to build great AI products.

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