The Paradigm Shift in AI Product Development: From Determinism to Probability

This article explores how general-purpose artificial intelligence (AGI) is disrupting the tech industry, particularly in software design, engineering, building, and growth. Traditional software development follows a deterministic model: known inputs produce expected outputs. However, AGI models are probabilistic, with outputs based on statistical distributions and inherent uncertainty. This renders traditional software engineering methods and metrics (like SLOs) obsolete. The author advocates for an empirical approach, using scientific methods and data-driven decision-making to build and iterate AI products, rather than relying on traditional engineering thinking. This requires organizations to transition from engineering to science, centering on data, and breaking down siloed departments for a holistic systems view.