Testing Exceptions and Failure Cases
Which steps can be automated safely, and where must the agent stop and hand control to a person? Build an evaluation set from real work and known exceptions, recording expected behaviour, evidence, escalation, and unacceptable outcomes.
What You Will Be Able to Decide
- Explain testing exceptions and failure cases in product and business terms.
- Apply this decision: Build an evaluation set from real work and known exceptions, recording expected behaviour, evidence, escalation, and unacceptable outcomes.
- Recognise this material risk: a convincing happy-path demonstration is mistaken for reliable behaviour under ordinary operational pressure.
- Use this review: Run the triage workflow with missing data, an unsafe request, an unavailable tool, and an item that needs escalation.
A founder or operator is deciding how an AI agent should participate in a real workflow without inheriting undefined authority. This lesson gives you a concrete question to take into a build brief, proposal review, or product decision.
Which steps can be automated safely, and where must the agent stop and hand control to a person? The course example is An agent that prepares a weekly customer support triage queue; use it to decide what evidence would justify the choice before a builder implements it.
What Does Testing Exceptions and Failure Cases Mean for Your Product?
A founder or operator is deciding how an AI agent should participate in a real workflow without inheriting undefined authority.
Use the illustrative service for this course (An agent that prepares a weekly customer support triage queue) to make the choice concrete. Which steps can be automated safely, and where must the agent stop and hand control to a person?
Technical term
Testing Exceptions and Failure Cases
Agent evaluation uses representative tasks, missing information, conflicting evidence, unavailable tools, unsafe requests, and recovery cases rather than one prepared demonstration.
How Should a Founder Use Testing Exceptions and Failure Cases?
For an agent that prepares a weekly customer support triage queue, ask what would happen if a convincing happy-path demonstration is mistaken for reliable behaviour under ordinary operational pressure.
For this decision, the useful standard is that the agent behaves predictably across representative work, respects its boundaries, and produces evidence a responsible person can review.
- Decision: Build an evaluation set from real work and known exceptions, recording expected behaviour, evidence, escalation, and unacceptable outcomes.
- Evidence to request: show that the agent behaves predictably across representative work, respects its boundaries, and produces evidence a responsible person can review.
- Owner: name who will respond if a convincing happy-path demonstration is mistaken for reliable behaviour under ordinary operational pressure.
- Record the result in the agent workflow specification, evaluation set, and operating record.
- Practical review: Run the triage workflow with missing data, an unsafe request, an unavailable tool, and an item that needs escalation.
How Do You Choose an Approach to Testing Exceptions and Failure Cases?
Which steps can be automated safely, and where must the agent stop and hand control to a person? Build an evaluation set from real work and known exceptions, recording expected behaviour, evidence, escalation, and unacceptable outcomes.
The risk is that a convincing happy-path demonstration is mistaken for reliable behaviour under ordinary operational pressure. Compare a simpler option with the proposed one, including who will operate either choice.
- Describe the user or business outcome that must be protected.
- Identify the most credible failure and its consequence.
- Compare the simplest adequate approach with one realistic alternative.
- Set a review point for when the decision may need to change.
What Evidence Should You Accept for Testing Exceptions and Failure Cases?
What Warning Signs Should You Look For?
- The proposal does not address this risk: a convincing happy-path demonstration is mistaken for reliable behaviour under ordinary operational pressure.
- Nobody can show whether the agent behaves predictably across representative work, respects its boundaries, and produces evidence a responsible person can review.
- The decision has no named owner or review point.
What Should You Ask a Consultant?
- What changes for the user if we choose this approach to testing exceptions and failure cases?
- How have we reduced or accepted this risk: a convincing happy-path demonstration is mistaken for reliable behaviour under ordinary operational pressure.
- Can you demonstrate that the agent behaves predictably across representative work, respects its boundaries, and produces evidence a responsible person can review?
- Who owns the result, and when will we reconsider it?
Key takeaway
Key Takeaway
Build an evaluation set from real work and known exceptions, recording expected behaviour, evidence, escalation, and unacceptable outcomes. Ask for evidence against the specific risk: a convincing happy-path demonstration is mistaken for reliable behaviour under ordinary operational pressure.