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SLOWCONOMICS

A manifesto for resource-conscious AI and a production pace we choose

v 1.0

Foreword — Breaking with Slopeconomics

We call it “Slopeconomics”: a system in which every gain in speed becomes a new obligation to produce more — more content, more features, more demands, faster.

In this system, AI becomes a permanent accelerator. We produce because we can, sometimes before asking what is worth producing.

We propose a different path: Slowconomics.

Our conviction is that working more slowly can be more responsible, have greater impact and, ultimately, help us make better use of our resources. Not because slowness is always a virtue in itself, but because it makes room for attention, foresight and choice.

An hour of thought can prevent days of unnecessary production.

Taking the time to look at what already exists can reveal what deserves to be built upon, improved or brought to wider attention.

A project we choose not to pursue can free up resources for an essential one.

We naturally stand for digital sufficiency: using the resources we need without treating consumption as a measure of ambition.

Like architecture that seeks the essential, we want fewer unnecessary elements, clear purposes and work that belongs in the world. We want to leave the time and space needed to understand it, use it, maintain it and make it last.

AI can play a part in this approach: for example, by helping us explore more thoughtfully what is worth deploying.

Ten commitments we invite you to make:

1. Don’t confuse speed with progress.

Before producing faster, ask what you are improving and for whom. Measure progress towards a useful outcome, not just the volume of output.

2. Start with the need, not the capacity to produce.

Just because AI can generate something does not mean it should. Look for what is missing before adding whatever is possible.

3. Anticipate before you accelerate.

Use AI to explore scenarios, compare alternatives and test your assumptions. Sometimes the most useful work is the work that prevents unnecessary effort.

4. Protect the time needed to create.

Not every hour saved needs to be filled with new tasks. Preserve time to observe, think, discuss and let an idea mature.

5. Don’t make urgency your operating model.

Respond to genuine emergencies. But when everything becomes urgent, question priorities, commitments and resources. Don’t automate the rush.

6. Account for all the resources needed to achieve a useful outcome.

A generated answer is not yet a useful outcome. Include checking, correction, integration and maintenance, as well as the material resources and energy involved.

7. Learn before you scale.

Experiment to answer a specific question. Share what you learn. Scale only when you understand well enough what the approach offers, its limitations and its risks.

8. Work in step with the world.

Your customers need time to choose what works for them and make it their own. Your teams need time to learn and adapt. The physical world needs time to manufacture, transport and repair. Don’t mistake these rhythms for delays to eliminate.

9. Retain control and remain accountable.

AI can make suggestions. You decide what to accept, what to check and what to decline. Preserve the ability to correct course, change tools and stop.

10. Share the gains instead of merely increasing the pace of production.

Use time saved to improve quality, working conditions and customer relationships, and to reduce resource consumption. Doing better can mean producing less.

Together

We do not choose to go slowly in every situation, but we do not see slowness as a weakness. In any case, we reject speed as the answer to everything.

We want to produce less when quantity undermines quality, but also to make better things when their quality can be recognised and valued. In every case, we want to produce in response to a genuinely felt need.

Beyond these choices, we want AI to help us regain control of our pace, rather than follow whatever pace it makes possible.

Let us choose not to produce faster than we can think.

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