To investigate potential causes of L2 performance deficits that correlate with age of onset, we use a computational model to explore the individual contributions of L1 entrenchment and aspects of memory development. Since development and L1 entrenchment almost invariably coincide, studying them independently is seldom possible in humans. To avoid this confound, we study neural network models that learn to solve gender assignment and agreement tasks in Spanish and French. We model the learner as a collection of recurrent cell assemblies that subserve working memory and are facilitated by trainable long-term connections. Varying the time-course over which assemblies and connections are added allows us to compare small, growing, child-like networks to fixed-size adult-like ones. Networks undergo variable-length exposure to L1 before L2 onset to control the amount of L1 entrenchment. This model, by allowing us independent control of both variables, lends us a novel glimpse of all sides of their interaction and affords a rare test of the less-is-more hypothesis. Network comparisons suggest that final L2 proficiency declines as L2 onset delays increase relative to L1, implicating an L1 entrenchment effect. However, aspects of memory development during learning play a key role in mitigating these impairments, lending support to less-is-more as a contributor to sensitive periods.