Decisions have consequences.
Most decisions look simple until the consequences arrive. AMuN maps the second and third order consequences of any decision before you make it — surfacing what you cannot see until it is too late to change.
Every decision has consequences that ripple outward — first order effects that are obvious, second order effects that are predictable if you look, third order effects that surprise everyone. Most decisions are made looking only at the first order.
AMuN maps all three before the decision is final. One question starts it: what decision are you trying to make? Everything else follows from that.
Open source. Available now. github.com/PTHMeridian/AMuN
Every decision. Every scale.
Consequence mapping applies wherever decisions have consequences that are not immediately visible. Which is everywhere.
Infrastructure investment, energy policy, healthcare reform, trade agreements — decisions affecting millions across decades. AMuN maps consequences before commitments are made and billions are spent.
Market entry, supply chain decisions, technology investment — choices that look straightforward often have regulatory, reputational and economic consequences that arrive years later.
Where to build a data centre. Whether to approve a pipeline. How to design a national energy transition. These decisions have water, climate, economic and community consequences that standard analysis misses.
Drug approval, treatment protocol changes, healthcare system reforms — decisions with economic, behavioural and equity consequences that compound over years and affect populations unevenly.
Career changes, financial decisions, educational paths — AMuN's consequence mapping applies at every scale. The question is always the same: what does this decision actually do?
Resource development on Indigenous territories, treaty implementation, energy infrastructure approvals — decisions with profound historical and community consequences that require full visibility before proceeding.
The people who designed Canadian residential school policy were educated, credentialed and certain of their conclusions. They were wrong — not because they lacked information but because they never examined their foundational assumptions. They optimised for a goal that was itself wrong.
AMuN does not tell you what goal to have. It shows you what the decision actually does — across all the systems it touches, over all the time horizons that matter — so that the assumptions are visible rather than hidden.