Project Governance
AI projects need a stop rule
A stop rule protects teams from endless experimentation without delivery evidence.
By JirakJ
6 min read
The moment to pay attention is not when somebody says "we should use AI." It is when the project keeps expanding because every demo reveals another possibility.
I would rather see one honest workflow map than ten polished AI use-case slides. From there, the work is to find the narrowest responsible improvement, not the loudest demo.
A small field test
Take one recent example of this workflow and replay it from request to finished output. The weak point will usually match the complaint: the project keeps expanding because every demo reveals another possibility.
Where the human stays
The human work is deciding what good means, what risk is acceptable and when a draft is not good enough. That judgment should be designed into the flow, not left to chance.
What to change first
Define what evidence will trigger build, pause, narrow or stop decisions. Do that before choosing a platform or adding another automation layer.
What I would keep
Keep the pilot decision rule. It becomes the reference point when the team forgets why the workflow was changed in the first place.
Monday morning checklist
- • Turn the next meeting into a decision log instead of another broad AI discussion.
- • Write down the artifact that would make the work reviewable: in this case, a pilot decision rule.
- • Decide who owns the next version if the first version works.
- • Mark the part of the workflow where human judgment must stay visible.
If this sounds familiar
Start with one workflow. FlowMason AI can map it, identify the right intervention, and define whether the next step should be a prototype, agent, documentation pipeline or delivery system.
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