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Testing the agent with scenarios

Day 17 of 30 · Generative AI 2026: Build AI Apps and Agents

One-liner: Validate the agent with real user scenarios.
Time: 20 to 30 min
Deliverable: Scenario Test Report

Learning goal

You will be able to: Test the agent with real scenarios and record results.

Success criteria (observable)

  • At least 5 scenarios are written.
  • Each scenario has expected outcomes.
  • Results are recorded with pass or fail.

Output you will produce

  • Deliverable: Scenario Test Report
  • Format: Scenario table plus notes
  • Where saved: Course folder under /generative-ai-2026-build-ai-apps-and-agents/

Who

Primary persona: Digital nomad validating agent behavior Secondary persona(s): Users relying on consistent output Stakeholders (optional): Collaborators

What

What it is

A small set of realistic scenarios that test whether the agent behaves as expected. It gives you evidence of what works and what fails.

What it is not

It is not an automated test suite or a replacement for user feedback. It is a practical check for early stage quality.

2-minute theory

  • Scenarios mimic how real users will try the product.
  • Expected outcomes make results measurable.
  • Regular scenario tests reduce regressions.

Key terms

  • Scenario: A realistic input and context a user might provide.
  • Expected outcome: The result you want the agent to produce.

Where

Applies in

  • QA checks
  • Feature validation

Does not apply in

  • UI color choices

Touchpoints

  • Test logs
  • Output reviews
  • Bug reports

When

Use it when

  • You finish a new agent workflow
  • Output quality is uncertain

Frequency

Before each release

Late signals

  • Repeated user complaints about output
  • Unexpected agent behavior

Why it matters

Practical benefits

  • Fewer production surprises
  • Faster debugging
  • Better user trust

Risks of ignoring

  • Low quality releases
  • Support overload

Expectations

  • Improves: reliability and confidence
  • Does not guarantee: perfect accuracy

How

Step-by-step method

  1. Write 5 realistic scenarios.
  2. Define expected outcomes.
  3. Run each scenario.
  4. Record pass or fail with notes.

Do and don't

Do

  • Use real inputs from your niche
  • Record failures clearly

Don't

  • Only test ideal cases
  • Skip documenting results

Common mistakes and fixes

  • Mistake: Ideal inputs only. Fix: Add messy inputs.
  • Mistake: No expected outcome. Fix: Define one per scenario.

Done when

  • Five scenarios are documented.
  • Expected outcomes are written.
  • Results are recorded.

Guided exercise (10 to 15 min)

Inputs

  • Your prompt spec
  • Sample user inputs

Steps

  1. Write 5 scenarios.
  2. Define expected outcomes.
  3. Run and record results.

Output format

Field Value
Scenario
Expected outcome
Result
Notes

Pro tip: Keep one scenario that is intentionally messy.

Independent exercise (5 to 10 min)

Task

Add one new scenario based on recent feedback.

Output

Updated test report.

Self-check (yes/no)

  • Are scenarios realistic?
  • Are outcomes clear?
  • Are results recorded?
  • Is there at least one messy input?

Baseline metric (recommended)

  • Score: 4 of 5 scenarios pass
  • Date: 2026-02-06
  • Tool used: Notes app

Bibliography (sources used)

  1. Software Testing Basics. ISTQB. 2024-01-01. Read: https://www.istqb.org/

  2. Agent Evaluation Guide. OpenAI. 2026-02-06. Read: https://platform.openai.com/docs/guides/evals

Read more (optional)

  1. Test Case Design Why: Simple structures for manual testing. Read: https://www.guru99.com/test-case.html