Course

Validating AI-Generated Code

Learning path outcomes

  • Develop unit and system tests with AI agents
  • Techniques for overseeing an AI testing plan
  • Discover best practices for reviewing AI-generated code
  • Learn how to provide feedback to AI, develop skills for repetitive tasks

Prerequisites

Experience building iOS apps from scratch, understand iOS testing, and have set up AI tools as per “Getting Started with AI-Assisted iOS Development”. You might need a subscription to Claude or ChatGPT for the full experience.

Learning path content

Using AI for Testing in iOS
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.
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