Mitigadaptation, tree-based synergy between the global climate change mitigation and adaptation agendas, has been slowly emerging in the 30 years of climate science–policy interaction with its various ups and downs, false starts and ever-increasing urgency of bending the climate curve. The potential contribution of agroforestry to the climate change mitigation and adaptation agenda has been slow to be recognized and effectively supported, as agroforestry existed on farm and in landscapes, but not yet in the world of policy documents, government statistics and sectoral lobby groups. The articulation of the 17 sustainable development goals that transcend sectoral claims for prioritization and call for results-oriented investment of public funds has made it easier for the adaptation and mitigation agendas to synergize. Especially where focus is on local livelihoods in green economies, creating space for a continuum approach to Agriculture, Forestry and Other Land Uses (AFOLU), within which trees outside forest and agroforestry can be recognized for what they are. The chapter takes stock of such changes, as they played out in Africa and Asia, especially, by reviewing three agroforestry concepts. The third, policy-oriented, agroforestry concept (AF3) deals with the existing forestry-agriculture dichotomy and creates space for a landscape land-use continuum, with results-based management, clarifying institutional versus vegetation-based forest concepts. The second, landscape-oriented, agroforestry concept (AF2) emphasizes multifunctionality of managing land and water for the full set of SDGs and awareness of natural and man-made disasters, supporting collective action and active participation in value chains. The first, farm-oriented, agroforestry concept (AF1) has its roots in risk management through diversity and is the primary level for climate change adaptation and climate-smart solutions. The concepts jointly interact with data, feedbacks, institutions and goals as part of complex, adaptive social-ecological systems.