Technological innovation obsolesces not only earlier technologies, but also the knowledge, skills, and expertise of the users of those technologies. Individual obsolescence is generally written off as the cost of participation in a vibrant capitalist economy, a small price to pay and part of the creative destruction that makes the entire system work. This paper takes a closer look at the individual costs of such obsolescence, through an investigation of the particular class of changes that present themselves subsequent to an individual’s adoption decision—updates, upgrades, service packs, redesigns, patches, bug fixes, feature releases, versions, and other putative enhancements crowding into the contemporary technological landscape with increasing frequency. Updates make up a much-neglected but significant proportion of the total number of changes that make their way to those who participate—whether whole-heartedly or with reservations, willingly or as the unsought consequence of their participation in the labor force—in the diffusion of modern technology. Diffused through an existing relationship between company and customer, updates do not fit the general model developed in diffusion theory and highlight the human cost of rapid technological obsolescence. Analysis of findings from usability testing and interviews reveals that the most significant elements of the update experience are, on the one hand, the construction of the adoption decision itself and, on the other, the experience of unlearning one set of routines in favor of a new closely related set. While not all such unlearning and relearning is onerous and labor-intensive, those routines that do not ordinarily rise into consciousness during use of a technology, such as memorized classification schemes and actions that have become incorporated into motor memory, are typically experienced as imposing an extremely high cost. Differentiating between types of unlearning, this paper offers a calculus of the individual costs imposed by different types of changes conveyed in updates, and it does so with two distinct goals. First, such a calculus may inform a technology design practice that is cognizant of high-cost unlearning and minimizes unnecessary penalties to the established user base in the diffusion of small change. Second, the update experience serves to illuminate a fundamental question of positioning that confronts the business ethnographer seeking to maximize his or her value to the corporation.