The acceptability of Human Machine Interfaces (HMI) is a central issue for numerous modern defense systems. The observed difficulty of complex computer systems (monitoring systems, drones, robots …) to sense the human world and interact with it in ways that emulate collaborative human-human work, has founded the DIRAC vision. Our interdisciplinary proposal addresses the question of understanding and mastering the development of “pleasant” yet efficient interactions using a very non-conventional approach. Instead of elaborating on existing complicated solutions, we take a radical simplification route taking advantages of recent discoveries in low-level human interactions and dynamical motor control. We argue that exploiting natural stability and adaptability properties of unintentional synchronizations and rhythmic activities can solve several of the acceptability problems of HMIs, and allow rethinking the current approaches to design them. In early communication among humans, synchrony was found to be a fundamental mechanism relying on very low-level sensory-motor networks, inducing the synchronization of inter- individual neural populations from sensory flows (vision, audition, or touch). Yet, to become a partner in a “working together” scenario, the machine needs also a minimal level of autonomy and adaptation. Predicting the rhythmic structure of the interaction will be used to build reinforcement signals to adapt the machine behavior: synchrony is caused by the interaction but also sustains the interaction itself in a circular way, as promoted by the enaction approach.