Decision Cartography

All our work is a series of decisions, small and big. Most of them we make without noticing: they settled long ago into how we work. We only see them when we ask AI to do a task for us, and find we have to explain ourselves, how we think and what we’ve already decided, because none of it was ever written down.

Decision Cartography is a way to record those decisions, so the way you work can be carried to any AI tool or agent. Explaining yourself to one assistant is bearable. But the moment you switch, bring in agents, or meet AI inside the tools you already use, you find yourself explaining it all again.

A map is only useful while it stays true. Decisions get refined, replaced and sometimes reversed, so the record keeps itself current from the corrections you already make, and it belongs to whoever made the decisions it holds.

The underlying principle is that you never think about Decision Cartography once your tools are connected to it. Your AI uses it in the background, recalling your decisions and capturing new ones.

For teams, it turns one person’s way of working into something everyone can build on. Knowledge passes between people through their AI, good practice spreads without anyone writing a playbook, and the gains from AI compound instead of starting over with every person and every tool.