Accelerators are entrepreneurial programs that attempt to help ventures learn, often utilizing extensive consultation with mentors, program directors, customers, guest speakers, alumni, and peers. Although accelerators have rapidly emerged as prominent players in the entrepreneurial ecosystem, entrepreneurs, policy makers, and academics continue to raise questions about their efficacy. Moreover, relevant organizational literature suggests that, even if accelerators are associated with better venture outcomes, results could be due to mechanisms other than learning, such as sorting or signaling. Drawing on mixed empirical methods that include proprietary data on the ventures accepted and “almost accepted” to a set of top accelerators, we find evidence that some, but not all, of the early accelerators we study substantially aid and accelerate venture development. We also find some evidence of sorting dynamics. These findings are corroborated using an auxiliary quantitative data set constructed from publicly observable data. Complementary qualitative fieldwork suggests a key driver of these accelerator effects is a novel learning mechanism we label broad, intensive, and paced consultation. The implication of these insights is that the practices of early accelerators represent a beneficial and likely replicable form of intervention that may also have relevance for independent entrepreneurs, educational programs, and corporate innovation.