Dynamic targeting (DT) is a spacecraft operational concept in which data from a lookahead instrument are utilized to intelligently point and reconfigure a primary instrument to maximize science return. By leveraging forward-looking sensors to dynamically guide narrow-swath, resource-constrained instruments, DT addresses a major inefficiency in space missions where high-value targets are transient or obscured by poor observing conditions. Rather than focusing on a single hardware technology, DT represents a foundational mission capability for future space architectures to optimize on-orbit energy, data volume, and hardware configurations. This adaptive framework directly enables a diverse suite of applications and mission concepts. DT facilitates lookahead cloud detection for cloud avoidance, which is especially useful for atmospheric retrieval missions such as OCO-2 and OCO-3, where cloud contamination prevents successful measurements. For active sensing architectures, it empowers targeted storm hunting to track the evolution of deep convective ice storms, as exemplified by the Smart Ice Cloud Sensing (SMICES) project, and supports configuring radar modes dynamically for specific cloud features, as demonstrated by the NIMBUS concept. Next-generation missions can also deploy DT to identify and capture rare, short-lived planetary boundary-layer (PBL) phenomena that evade traditional pre-planned scheduling. Finally, this capability can extend to deep space exploration, allowing assets to autonomously track events such as comet plumes. Backed by comprehensive simulation studies and an operational demonstration on CogniSAT-6 since 2025, we demonstrate how DT fundamentally shifts space operations from passive, ground-dependent tracking to autonomous, onboard decision-making that increases mission productivity and science return.