In order to implement intelligent systems that exhibit autonomous behavior, the system must develop its own situation awareness and ability to execute the decisions being made. To model these end-to-end decision loops, we propose a framework that combines situation awareness, decision-making, and action-planning theories into one decision ladder that helps to understand the requisite anatomy and ergonomics of intelligent systems. This Situation Awareness and Decision Execution (SADE) Ladder acts as a catalyst bringing together different research disciplines specialized in each of the three referenced domains. This synergistic view across multiple research agendas manifests in a conceptual framework to understand better the interaction dynamics in human-AI interactions and the importance of transparency and explainability in multi-agent networks to help the human experts understand the locality of artificial system intelligence and the underlying rationale of system-generated decisions and action plans. Identifying the different cognitive demands and sub-functions within the SADE Ladder enables practitioners to derive the appropriate requirements from cognitive work analysis and design intelligent systems for workplaces that are trusted and accepted by their users.