BabyTrack is a legacy iOS project that mixes Objective-C, Swift, UIKit, and SwiftUI. In this lesson, you will use AI to map the unfamiliar codebase, but you will treat its answers as investigation leads rather than facts. You will check important claims against the source and distinguish real technical debt from age, language, framework, or style preferences.
Xcode version: This lesson was recorded using Xcode 27.0. If you use another Xcode 27 build, some interface details, including AI model-selection controls, may look different.
What you will do
Ask AI for a focused map of the app’s entry points, screens, data flow, dependencies, and tests.
Verify important claims using the files cited in the response.
Remove unsupported findings and prioritize verified technical debt.
Produce a complete codebase-assessment.md file.
Materials
Project/Starter/BabyTrack/BabyTrack.xcodeproj
AI Resources/Lesson Prompts/lesson-1-prompts.md, if you want to copy the prompts instead of typing them
An AI assistant that can inspect the BabyTrack project
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Output
The completed codebase-assessment.md is available in Project/Final.
See forum comments
This content was released on Oct 21 2026. The official support period is 6-months
from this date.
Prepare to explore BabyTrack, verify AI-generated findings, and produce an evidence-backed codebase assessment.
Download course materials from Github
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