Policy and investment decisions in highly connected, developing regions can have implications that extend beyond their initial objectives of national development and poverty reduction. Local level decisions that aim to promote trajectories toward desirable futures are often transformative, unexpectedly altering factors that are determined at higher regional levels. The converse also applies. The ability to realize desirable local futures diminishes if decision-making processes are not coordinated with other influential governance and decision levels. Providing effective support across multiple levels of decision making in a connected, transformative environment requires (a) identification and articulation of desired outcomes at the relevant levels of decision making, (b) improved understanding of complex cross-scale interactions that link to potentially transforming decisions, and (c) learning among decision makers and decision influencers. Research implemented through multiple participatory modalities can facilitate such relevant system learning to contribute to sustainable adaptation pathways. We test application of a systematic policy engagement framework, the Challenge and Reconstruct Learning or ChaRL framework, on a set of interdependent development decisions in the Mekong region. The analysis presented here is focused on the implementations of the ChaRL process in the Nam Ngum River Basin, Lao People's Democratic Republic and the Tonle Sap Lake and environs, Cambodia to exemplify what cross-scale and cross-sectoral insights were generated to inform decision-making processes in the wider Mekong region. The participatory process described aligns the facilitated development of scenarios articulating shared future visions at local and regional levels with agent-based simulations and facilitates learning by contrasting desired outcomes with likely, potentially maladaptive outcomes.