DECISION ARCHITECTURE

Make consequential AI and platform decisions with evidence, not momentum.

Decision Crafters helps technology leaders structure uncertain decisions, separate evidence from assumptions, compare viable alternatives, and identify the smallest responsible next action.

PATH ONE

Explore the research

Evidence-labelled briefs, syntheses and method notes. Enter →

PATH TWO

See whether the Diagnostic fits

A bounded review of one architecture decision. Discuss the decision →

Latest

Research Hub →
2026·10·24

How to Define Stop Conditions Before an AI Pilot Starts

Before funding an AI pilot, agree in writing what would stop it: the evidence, the owner, the review date, and the action attached to each condition.

2026·10·24

When Kubernetes Is the Wrong First Answer for an AI Workload

Before approving a new cluster for an AI experiment, ask which requirement makes it necessary — and choose the smallest route that meets the workload's actual constraints.

2026·10·23

What Platform Leaders Should Measure Before Adding Another AI Tool

Before adding another AI tool, measure outcomes, workload quality, reliability, useful-outcome economics, authority failures, and actual usage.

2026·10·16

The Control Plane for Human–AI Production Decisions

A practical architecture pattern for separating what an agent can do from what it is allowed to do AI systems do not become production