When a delivery agency persuades a bicycle courier worker to accept a certain job, it does so by revealing the right amount and kind of information. The goal is to reward both the agent as well as the worker accordingly. In this paper, we model the act of persuasion in information-theoretic terms. The main emphasis is on an approach inspired by the so-called information bottleneck problem. We derive results about the structure of the resulting optimization problem and present solutions for certain special cases. An algorithmic perspective is also developed, with potential applications in learning. Finally, we outline an alternative complementary problem formulation leveraging remote rate-distortion theory.