Mechanism
Shared interfaces and reusable artefacts allow a network to accumulate capability no participant owns alone.
Enabling conditions
- Local experimentation is permitted
- Evidence can travel between nodes
Failure modes
- Learning remains local
- Bad practice spreads without review
Early signals
- • Experiments repeat across sites
- • Documents grow but workflows do not change
Countermeasures
- • Capture evidence and conditions
- • Encode review and forgetting triggers
Diagnostic questions
- 1.What makes a result reusable?
- 2.How is obsolete knowledge retired?