Deadbots—AI systems designed to simulate the dead—clarify how generative AI reshapes temporal sense‑making. Operating in the “digital limit situation” of loss and finitude, they neither preserve memories nor store archives; they sever material traces and outsource the work of remembrance to automated interaction, ultimately fostering forgetting. The talk frames deadbots as a convergence of two traditions. From cybernetics, they inherit the “empty archive,” where feedback replaces retention and provenance is erased during model training. From technological spiritualism, they draw on practices that use technical mediation to confer authenticity, echoing nineteenth‑century séance boards and mid‑twentieth‑century Electronic Voice Phenomena. In both cases, technology gains authority through its apparent objectivity and opacity, inviting speculation about contact with the absent. Yet deadbots diverge from their spiritualist lineage by eliminating the interpretive labor once required to sustain such connections. The user’s role is reduced to passive consumption of a corporate service, while the system’s probabilistic token prediction turns remembrance into chance encounters. Consequently, deadbots function as engines of presentism—the endpoint of an “automation of memory” that dissolves the past into ever‑renewed simulations.