Calibrating Testing to Risk
Not everything needs the same rigor. The skill is to match how hard you test to how much a mistake would cost — so your effort lands where it actually matters.
The Risk Lens
Before you decide how to test, ask: what happens if this is wrong? The answer sets everything else.
- A typo in a rough draft is a shrug — you fix it and move on.
- A wrong medical or financial answer can harm someone before anyone notices.
- Same model, same code — but the cost of being wrong is worlds apart.
Calibrate the Effort
Once you know the stakes, scale the testing to fit them — light where it is cheap to be wrong, heavy where it is not.
Where to Spend
Your testing budget is finite. Put it on the paths where a mistake is expensive to undo.
- Anything that touches money — charges, transfers, refunds.
- Anything that touches safety — health, legal, physical action.
- Anything that touches privacy — personal or sensitive data.
- Anything irreversible — deleting, sending, publishing.
It All Scales With Risk
This lesson ties the course together. The big tools you already met are not separate rules — they are all dialed to risk.
- Module 4's tradeoffs — how much to invest in a feature.
- Module 7's guardrails — how tightly to constrain the model.
- Module 8's evals — how thoroughly to measure quality.
Build It
How to implement: rate each feature of your tool low, medium, or high risk — then give the high‑risk ones the most eval and review, and let the rest stay light.
- Weekly AI Tasks tracker — reading tasks is low risk; anything that deletes or sends is higher, so test and gate those harder.
- Personal brand site — publishing a false claim is the real risk, so factual verification gets the most rigor.
What you learned
Match testing to the cost of being wrong: light checks for low‑stakes, reversible work; heavy evals, review, and guardrails where money, safety, privacy, or irreversible actions are on the line.