Teachers are called upon to address a growing number of educational and societal challenges. The time they can devote to ongoing teacher professional development is limited. Yet, with rapid changes in society and technology, particularly AI, the problems are compounding, almost daily. To provide teachers with scientific advice on how to teach, assess, and support children, educational researchers initially deployed external curricula, instructional strategies, and assessments where poor impact was viewed as a lack of adoption by teachers (a “theory to practice” problem). Early in the twenty-first century, a field engineering model emerged where teaching practices and artifacts were cocreated by researchers and practitioners in classroom settings (i.e., design-based research, DBR). In parallel, we saw the emergence of teacher networks to support teachers using distributed expertise (e.g., Japanese Lesson Study/JPL and Networked Improvement Communities/NIC). This chapter proposes an integration of DBR research methods and the network properties of JPL and NIC to tackle the many problems faced by teachers. The model is called a knowledge-building action network (KBAN). The KBAN may be viewed as concentric circles with individual teachers in the center (DBR), supported by aligned teams of teachers (JPL), and in the outermost circle, professionals who address problems of resources and policies. Yet, the networks interpenetrate interpenetrate with practitioners and researchers at each level collaborating to propose, design, and test solutions to chronic problems of practice. The social and logistical problems of enacting a KBAN are significant. The chapter ends with an outline of how current generative AI (genAI) tools may be poised to help make a KBAN functional and contributory.