A canonical setting for non-monetary online resource allocation is one where agents compete over multiple rounds for a single item per round, with i.i.d. valuations and additive utilities across rounds. With n symmetric agents, a natural benchmark for each agent is the utility realized by her favorite 1/n-fraction of rounds; a line of work has demonstrated one can robustly guarantee each agent a constant fraction of this ideal utility, irrespective of how other agents behave. In particular, several mechanisms have been shown to be 1⁄2-robust, and recent work established that repeated first-price auctions based on artificial credits have a robustness factor of 0.59, which cannot be improved beyond 0.6 using first-price and simple strategies. In contrast, even without strategic considerations, the best achievable factor is 1-1/e≈0.63. In this work, we break the 0.6 first-price barrier to get a new 0.625-robust mechanism, which almost closes the gap to the non-strategic bound.