In the past decade, our appreciation of the contribution of innate lymphoid cells (ILCs) towards homeostatic and inflammatory responses has advanced tremendously; however, because ILCs and T cells both rely on a highly overlapping set of genes for development, models of ILC-specific deficiency have lagged. To establish selective tools requires an understanding of the shared and distinct regulators of ILC development. Recent work from our lab and others has advanced an understanding of the precursors that comprise the ILC developmental hierarchy and the expression of transcription factors driving this progression. Analysis of chromatin accessibility and genome editing via CRISPR/Cas9 have also enabled the identification of cis-regulatory elements governing ILC development. Yet, many of the ILC precursors described to date have been recognized as far more heterogeneous populations than initially proposed, a result of the limitation in available tools to resolve such complexity. Moreover, the general lack of clarity has hindered an assessment of the dynamic changes in genome accessibility occurring between precursor and product. We utilized CRISPR/Cas9-mediated transgenesis to generate novel combinatorial transcription factor reporters to address precursor heterogeneity and uncovered intermediate specified precursors to the ILC and Lymphoid Tissue-inducer lineages. From these results, we established a revised hierarchy of ILC development and used our multi-transcription factor reporter mice to isolate refined precursor populations and compare changes in chromatin accessibility over developmental time. At the Gata3 locus, we discovered a dynamic region responsible for regulating the high level of GATA3 expression in ILC2s that is necessary for their proper development and function at homeostasis and following type 2 inflammation. In sum, the revised hierarchy of ILC development and chromatin accessibility data for intermediate ILC precursors will enable the identification of crucial regulators of ILC development and inform the generation of models to better understand ILC biology.