Deep-tech ventures face both technological and commercial uncertainty, yet little is known about how entrepreneurs should sequence exploration across them. I examine how parallel or sequential exploration shapes venture outcomes in asset-intensive settings, arguing that exploration sequencing involves a temporal trade-off between external signaling and internal capability development. Parallel exploration facilitates external validation by generating market signals that reduce information asymmetry, but weakens organizational learning through divided attention and premature technological lock-in. Sequential exploration enables deeper technological learning and absorptive capacity, improving long-run performance. Using a novel longitudinal dataset of 13,785 hardware ventures, behavioral measures derived from patent and trademark timing and the diffusion of additive manufacturing (3D printing) as an exogenous technological development, I find a clear temporal trade-off. Parallel exploration increases the likelihood of early resource mobilization and commercialization, whereas sequential exploration generates stronger long-run innovation and venture performance. These findings identify exploration sequencing as a fundamental strategic choice under multiple uncertainties and establish boundary conditions for entrepreneurial experimentation, including lean startup methods, in asset-intensive firms.