Standard genetic programming genotypes are generally highly disorganized and poorly structured, with little code replication. This is also true of existing developmental genetic programming systems [9, 18], which exploit regularity by using procedures, functional modules, or macros and parameters passing. By contrast, in biological developmental evolution, nature works through code duplication to generate modularity, regularity and hierarchy. Previous developmental approaches have only one level of evaluation for each individual an approach which limits the advantages of modularity to the species rather than the individual, and hence inhibits selection of modularity. We argued in [10, 4] that evaluation during development is necessary for structural regularity to emerge. To confirm the benefits of developmental evaluation and the contribution of code duplication to nature, our new developmental process uses a new representation. Developmental Tree Adjoining Grammar Guided GP (DTAG3P) uses L-systems to encode tree adjoining grammar guided (TAG) derivation trees, and has been investigated in [4]. We have demonstrated scalable solutions to difficult families of problems, and have evidence that this performance is linked to the generation and exploitation of structural regularities in the solutions.