This whitepaper is the Methodological Layer of a four-paper publication architecture documenting the Decision Architecture discipline (Hernandez and Montero 2026, DOI: 10.5281/zenodo.19831515). It documents the foundational technique that responds to the structural conditions established in the Diagnostic Layer: backcasting and the dual lens, applied to consequential decision-making, with a decision architecture artifact as its output. The paper reframes backcasting (an established methodology in the energy and sustainability planning literature) by specifying the desired future state as an inspectable end-condition. The dual lens principle, drawing on the multi-perspective tradition in decision sciences, requires that any consequential decision be examined through paired forward-looking and backward-looking perspectives held simultaneously. The combination produces a decision architecture artifact: a structured object documenting the decision, its assumptions, its desired future state, its current-state grounding, and the path between them. The methodology specifies the conditions of AI participation as a structural response to the AI-amplification mechanisms documented in the diagnostic. The contribution is the codification, not the invention; the technique synthesizes the established backcasting literature with the multi-perspective tradition and applies the synthesis to consequential decision-making. The methodology specifies what any framework operationalizing the technique must contain. Frameworks that operationalize the technique at specific scales, including the forthcoming Solo Decision Architecture (SDA) framework and Business Decision Architecture (BDA) framework, are evaluated against these methodological requirements.