Emerging applications and technologies such as vehicle-to-everything (V2X), edge-computing, and artificial intelligence have emphasized the demand for low-latency and deterministic communication. Although the 5G network has taken several efforts to fulfill this demand, such as with 5G-Time-Sensitive Networking (TSN) integration and DetNet, these efforts must be significantly expanded in 6G to fully achieve end-to-end deterministic communication. In this paper, we explore the problem of programmable deterministic communication in the new architecture of 6G. To deal with this problem, we rely on TSN, which has been proven to be a promising solution for deterministic communication. We take V2X as a use case, then investigate the two greatest challenges of this use case: low-latency communication and programmable network management for deterministic communication. To deal with these challenges, we introduce two solutions: (i) TSN low-latency scheduling supported by Multi-Agent Deep Reinforcement Learning, and (ii) programmable network management supported by SDN and joint cloud-infrastructure control. For each solution, detailed architecture and functionality design are presented. We show their high feasibility, applicability, and potentialities through comprehensive definitions, detailed explanations and in-depth qualitative analysis.