Foresight triage: what to do when you’ve only got six hours

Last Monday I was a mentor at Hack for the Futures, a one-day AI for Climate Action hackathon during London Climate Action Week 2026. The premise was simple and demanding: bring together young developers, researchers, designers, and climate experts, and ask each team to produce a working prototype and a future scenario tied to climate action.

They had six hours.

That is not six hours for a foresight exercise. It is six hours for everything: defining the problem, forming the team, building the prototype, thinking about users, preparing the pitch, and working out whether the idea has any credible future relevance.

The teams were impressive: smart, committed, technically capable, and moving at extraordinary speed. But when they hit the foresight element, two things tended to happen.

Some looked at the Futures Toolkit (declaration of interest – SAMI helped write this with GO-Science).  Sensible, obviously. The Toolkit is designed to be accessible and includes a set of tools and seven suggested pathways for different purposes. Other teams asked an AI assistant, which produced the kind of immaculate full-fat futures process that begins with horizon scanning, proceeds through driver mapping and scenarios, and ends with elegant recommendations sometime next quarter.

Both routes were useless in the circumstances.

This was not a failure of the Toolkit, or of AI. It was a mismatch between method and context. A proper foresight process needs time, framing, facilitation, and some shared understanding of what the tools are for. These teams had none of that. They had a clock, a pitch deadline, and a climate challenge.

So the useful thing was not to teach them foresight. It was to triage it.

By that I mean a short, structured intervention that helps a team under pressure answer enough futures questions to improve the work in front of them. It does not aim for methodological purity. It aims to prevent obvious mistakes, clarify the future context, and give the team a clearer account of why their innovation might matter. There a three basic questions:

First: where does your innovation land in time? Is this something for next year, 2030, 2040, or a world after major climate disruption has already changed systems around it? A prototype can be built in a day, but its real value may depend on infrastructure, regulation, user behaviour, finance, or climate conditions that are still emerging.

Second: what kind of world does it land in? Many teams started from the implicit assumption that the future would be like the present, with better tools. That is rarely good enough for climate work. As we learned at other events during the week, heatwaves and no aircon can cancel projects (and trains) even now, let alone in the future.

Third: what should the team change now, once that future context is visible? That might mean altering the user group, changing the data assumptions, adding a governance feature, identifying a dependency, narrowing the claim, or turning a generic climate solution into something much more specific and credible.

The tools I used were deliberately simple.

A Futures Wheel helped teams think in first-, second-, and third-order effects. If your tool improves energy efficiency, what happens next? Who saves money? Who loses revenue? What behaviours change? What new risks appear? Where are the rebound effects?

SWOT was useful, despite my general dislike of it, because everyone understands it. The important move was to keep the distinction clean: strengths and weaknesses inside the project; opportunities and threats in the external environment.

PESTLE acted as a checklist. Technical teams are naturally drawn to the T. Climate action does not live in the T alone. Political permission, economic incentives, social trust, legal constraints, and environmental realities all matter.

The cone of plausibility helped them move away from single-point prediction. The further out they were placing their idea, the wider the range of plausible conditions became. For technically minded people, this was sometimes the hardest step. They liked data and forecasts. Perfectly reasonable. But good foresight starts where the data become insufficient and the uncertainty increases.

Finally, I used a simple top/middle/bottom view of future impact. At the top: what would success look like if the idea really worked? What system would it improve? Who would benefit? What would be different from today? At the bottom: what could go wrong? What dependencies could fail? What assumptions might break? Who could be excluded, harmed, ignored, or simply not persuaded? In the middle: what is the minimum credible version that would still be worth building? As an old mentor of mine used to say, “good enough will do”. In this context, “good enough” meant something quite demanding: clear enough to explain, robust enough to defend, and practical enough to develop further.

These were not sophisticated techniques. That was the point. Under time pressure, sophistication can become self-indulgence. The task was to give teams enough futures discipline to improve their project without drowning them in method.

There is a broader lesson here. The Futures Toolkit contains proper, structured pathways for more considered work. Those pathways matter – methodologically tight, proven in practice, extensively peer-reviewed, and deployable at scale.

The lesson I took away, though, was that there is space for something lighter, faster, and more interventionist: foresight triage for teams under intellectual and time stress.

It will not produce a robust scenario set. It will not replace horizon scanning. It will not give you a fully tested strategic option. But it can materially improve the quality of thinking. It can help teams notice the world around their innovation, not just the object they are building. It can expose dependencies, surface risks, sharpen opportunity, and make claims more credible.

When you’ve only got six hours, triage may be all you have time for. But done well, it is not a poor substitute for foresight. It is the first useful act of foresight: finding the future questions that matter most, before the bell goes.

Written by Jonathan Blanchard Smith, SAMI Director and Fellow

The views expressed are those of the author(s) and not necessarily of SAMI Consulting.

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