A futures literacy calls for a familiarity with manifold models of change and an ability to navigate between them as appropriate. The path of least resistance is often to ignore any change, continue business as usual (sometimes beneficial, other times a disastrous strategy). A resilient approach encourages a more fluid response with the aim of returning to a normal or stable state as soon as possible. An adaptive system would incorporate change and transform itself into a new (ideally improved) state in response to that change. Finally, a revolutionary change is one which radically transforms the system or significantly destabilises it in such a way that returning to a previous state is usually impossible. Vinay Gupta suggests the need to clarify when each of these different responses to change might be appropriate and suggests a way to balance long-term visions with crisis responses of resilience, revolution and adaptation, which are inevitably focused on short-term fixes.

Strategies and plans based on preferred futures can turn out to be wishful thinking, yet they are also reservoirs of the values and principles of the people involved. Without them responses to change can only be reactive. However, when held too tightly in times of rapid change, long-term strategies can easily become obsolete or counterproductive, preferred futures might turn out to be impossible futures. Conversely, improvised tactics might be what's needed for survival, but they are usually immediate, non-systemic solutions. How can we keep preferred futures alive, while at the same time responding appropriately to current change? We believe the answer lies in tighter feedback loops between vision and adaptation, where knowing how to respond to a situation comes from iterative prototyping of alternate and preferred futures.

In the field of design the creative process (which often takes uncertainty as a given) tends to be iterative. Ideas are usually developed cyclically rather than linearly, from a minimal working version into something fully developed. Each iteration is usually tested, if possible with actual people and in real-life settings. Prototypes are evaluated and adjusted if needed. Well performing prototypes can then be extended with new features. A design can always fall back onto a previous iteration, so the more testing, the more resilient, or well adapted the design can become.

Examples of futures testing include disaster drills and war simulations. While drills for potential disasters have become an established practice, there aren't many examples of drills or exercises for other, less disastrous types of futures. Disaster drills may be good for training short-term tactics and responses, but don't usually examine long-term visions. War games and military simulations can be appropriate for teaching strategy and planning but are less well suited for civilians. Drills designed for future preparedness would ideally incorporate a multiplicity of futures (preferred and otherwise) and a layered approach to time. They would require short-term tactics as well as adaptive long-term strategies. Testing alternative or preferred futures through experiential exercises can foster feedback-loops between ideas and experiences, encouraging a non-deterministic attitude leading toward visionary adaptation.