Coming soon. This chapter is outlined below and being written. It's part of the AI Skills library.
What this chapter will cover
- How to read each causal link in a theory of change and ask whether it rests on evidence or assumption.
- Where to spot the leaps of faith — the arrows from activities to outcomes that no data supports.
- How to separate assumptions that are documented and tested from those quietly taken on belief.
- How to turn the audit into a prioritized list of the weakest links worth strengthening first.
- Approach prompt: "Review this theory of change and flag every causal link that rests on belief rather than data, then rank them by how much weight the model puts on each."
Why it matters
Flags links resting on belief, not data.
