【Description】This research note reinterprets the P versus NP problem through the lens of temporal structure rather than computational speed. By focusing on when contradictions become observable during exploration, the paper introduces exposure time as a unifying concept linking SAT, NP-completeness, polynomial-time reductions, and the limits of heuristic and AI-driven search. The work does not claim a proof of P ≠ NP. Instead, it provides a structural explanation for why exploration persists across representations and algorithmic paradigms. The proposed framework positions P versus NP as a boundary condition on how information, choice, and time interact in combinatorial systems. 【Abstract】The P versus NP problem is traditionally framed as a comparison between the efficiency of solution discovery and verification. This paper proposes a structural reinterpretation based on the temporal behavior of contradiction emergence during exploration. We introduce the notion of exposure time: the point at which a partial assignment becomes provably non-extendable. While problems such as 2-SAT allow exposure time to be advanced to the moment of local choice, NP-complete problems like 3-SAT exhibit delayed exposure, where contradictions emerge only after combinations of choices align. Through minimal structural examples and a reinterpretation of polynomial-time reductions as exposure-time preserving mappings, we argue that NP-completeness reflects robustness of delayed contradiction exposure under representational change. This leads to an exploration preservation principle: when the meaning of choices is generated through combination rather than isolation, exploration cannot be eliminated in principle. We further discuss implications for heuristic search, learning-based systems, and AGI, suggesting that while exposure time may be partially advanced, delayed exposure remains structurally unavoidable. 【Keywords】P versus NPNP-completenessSATreductionsexplorationexposure timestructural complexityAGI