Pause and practice.
Course exercises matched to the book. Open a lesson, copy its prompt and artifacts into your AI coding agent, and judge what actually happened. These pages do not call an AI service themselves.
Chapter 1
Find bugs in one homepage
Give your agent a screenshot, console evidence, and network evidence from the deliberately imperfect TestBucks homepage. Judge whether its findings are valid.
Try this exercise →Chapter 2
Crawl and check
Discover the small TestBucks fixture, capture its pages, and check the artifacts. Keep the crawl bounded.
Try this exercise →Chapter 2
Compare pages and dedupe
Attach multiple screenshots and a bug list. Consolidate shared defects without losing affected-page evidence.
Try this exercise →Chapter 3
Resize text and review meaning
Compare broken and reflowing layouts, inspect misleading alt text, and ask for evidence-backed accessibility findings.
Try this exercise →Chapter 7
Record once, replay intelligently
Use two prompts: perform a browsing journey and save its OpenTest.ai intent, then replay that intent against the current interface.
Try this exercise →Chapter 9
Turn legacy scripts into intents
Copy a sample Playwright or Selenium test and convert it to the OpenTest.ai intent format. Check that the original assertions survive.
Try this exercise →Chapter 11
Make the app more testable
Copy the TestBucks HTML and ask for stable data IDs, useful diagnostics, and controllable synthetic test data. Review the changes.
Try this exercise →Chapter 12
Inject a payment timeout
Use an isolated practice replica and mock payments. Inject a fault, trigger it through the UI, and check recovery without duplicate simulated charges.
Try this exercise →Chapter 13
Find risks in source code
Copy the synthetic checkout service and requirements. Find missing validation, unsafe retries, and risky dependencies, then rank the next tests.
Try this exercise →Chapter 13
Challenge the implementation
Try the last-name form and generate boundary tests from its source. Separate the implemented limit from the rule the product needs.
Try this exercise →Chapter 14
One homepage, three perspectives
Review a coffee-shop homepage as a rushed commuter, keyboard-only user, and first-time customer. Compare qualitative feedback and ratings.
Try this exercise →Chapter 22
Build a quality report
Copy the pass/fail grid and generate a branded report with an executive summary that preserves failures and untested scope.
Try this exercise →Chapter 22
Build a release-confidence report
Combine risks, results, untested areas, and missing evidence into a release recommendation and prioritized next tests.
Try this exercise →Chapter 24
One agent, several browser workers
Give each worker an isolated context and a distinct task. Collect actual results; do not present sequential execution as parallel work.
Try this exercise →Chapter 24
Run parallel customer journeys
Give synthetic customers different orders. Combine their results and dedupe shared findings. Create cloud resources only with an approved budget.
Try this exercise →Chapter 26
Test yourself against AI
Give yourself and AI ten minutes, then compare findings, overlap, and differences. Judge the evidence, not just the bug counts.
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