Performance vs. Learning

Performance is what a practitioner can do now, under current conditions, with available tools. Learning is the change in underlying cognitive structures that enables future performance under different conditions, in novel situations, or without the tools currently available. The two are distinct and often inversely related — a finding established across decades of research in the learning sciences and elevated to central importance by the AI transition. AI tools optimize for performance: they produce the best possible output given the user's input. They do not optimize for learning, and in their default mode of operation they systematically remove the conditions under which learning occurs. This produces a population of practitioners whose visible output is high and whose underlying capability is eroding — a mismatch that remains invisible until circumstances reveal it, typically at the worst possible moment.