This module focuses on the testing side of Agentic Development. Rather than teaching
you how to write tests by hand, since the code itself is now written by AI agents, it
focuses on how to instruct an agent about which tests to write and why, and on
prioritizing tests before implementing a fix. You’ll consolidate the audits produced by
the previous module into a concrete, prioritized unit-test plan and use Conductor to
write those tests in parallel. Then you’ll use Xcode 27’s simulator MCP to have an AI
agent simulate human behavior in a running app by executing plain-English test steps
itself, and have that same agent debug the app directly through breakpoints and the
console.
This module does not cover how to write tests manually, and treats “write unit tests”
or “increase coverage” as anti-patterns to avoid — every test in this module traces
back to a specific, reasoned finding.
Prerequisites: Completion of “iOS Feature Implementation Using AI” module.
By Ehab Amer.
Consolidate the audits from the previous module into a concrete, defined test plan,
then guide an AI agent to write unit tests against that plan with a specific goal in
mind — not an open-ended coverage target.
Use Xcode 27’s MCP-driven simulator control to have an AI agent simulate human behavior
in your running app by executing plain-English test steps itself, and let the agent
debug the app directly through breakpoints and the console.
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30.0M · $12.50 · Claude Sonnet 5, Claude Sonnet 4.6 · Sep 2026
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