In fluctuating coastal oceans, ecosystem resilience is generally thought to depend on functional redundancy, the assumption that taxonomically distinct microbes perform interchangeable metabolic roles to buffer environmental changes. However, whether this redundancy is realized at the level of active gene expression has remained unclear. Using an autonomous drone array, we performed ultra-high-frequency metatranscriptomic sampling every two hours over 72 hours in Daya Bay, China. By resolving the active transcriptional landscape into six distinct temporal modules, we found that more than 90% of transcribed gene clusters turned over completely within ~2-hour windows. Community composition strongly predicted metabolic function, with the tightest coupling at the genus level (p < 0.0001). Functional continuity was maintained not through interchangeable generalists, but via a precise sequential relay of temporal specialists, each optimized for narrow, transient microniches. Deep-learning analysis of the psbA gene pool further revealed that cyanophages repeatedly introduced distinct protein variants to sustain photosynthesis during peak irradiance. Although genomic redundancy may exist in the potential gene pool, it is largely absent from the actively expressed metabolic landscape, which instead operates as a finely synchronized, clock-like succession of time-bound specialists. This framework provides a more predictive basis for understanding how coastal microbiomes respond to rapid environmental fluctuations.