AI Tab Completion: Cursor, Copilot, and Inline Suggestions

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-tools-ai-coding-tab-completion-r13a2-creators

1. A developer opens a single file in their editor and starts typing. Which capability is most accurate about what the inline AI can suggest?

   1. It can reference variables and functions from other files in the same project without any additional setup
   2. It can automatically fix syntax errors in existing code across all files
   3. It can complete the next few lines of code based on what it sees in the current file
   4. It can rewrite entire functions to follow different design patterns

2. Which of these tasks is inline AI LEAST suited for compared to a chat-based AI assistant?

   1. Predicting the next line of code in a loop
   2. Suggesting import statements for visible function calls
   3. Completing repetitive test cases with similar structure
   4. Refactoring code to use a different architectural pattern

3. Why should a developer always run or compile code after accepting an inline AI suggestion before committing it?

   1. Because the AI always produces syntactically correct code
   2. Because the compiler will automatically accept all suggestions
   3. Because the editor will crash otherwise
   4. Because inline AI can suggest method names or functions that don't actually exist

4. A developer wants the inline AI to use a function defined in a different file that isn't currently open. What must they do?

   1. Use chat to ask about the other file, then switch to inline completion
   2. Nothing special—the AI can see all files in the project automatically
   3. Add explicit context such as pasting the function or opening that file
   4. Type the function name manually first so it becomes visible

5. Which scenario demonstrates the strongest use case for inline AI tab completion?

   1. Deciding between two different data structures for a feature
   2. Generating a high-level project plan
   3. Completing a series of similar getter methods following a pattern
   4. Asking the AI to design an entire new class architecture

6. A student notices their inline AI suggests code that perfectly matches their project's existing naming style (camelCase, specific prefixes, etc.). Why does this happen?

   1. The AI learns naming patterns from the local code context it can see
   2. Naming style is determined by the editor, not the AI
   3. The AI always defaults to camelCase regardless of project style
   4. The AI reads the project's configuration files for naming rules

7. When is it appropriate to switch from inline AI completion to a chat-based AI?

   1. When you need to type a single variable name
   2. When completing the next line of a for loop
   3. When you need a simple typo fix
   4. When you need architectural guidance or need to understand code across multiple files

8. What is the primary limitation that distinguishes inline AI from chat-based AI assistants?

   1. Inline AI requires internet access while chat AI works offline
   2. Inline AI only sees and processes the code currently visible in the editor
   3. Inline AI cannot generate comments
   4. Inline AI is slower than chat AI

9. A developer accepts an inline AI suggestion that looks correct but causes a compile error. What most likely happened?

   1. The compiler is outdated
   2. The file was saved incorrectly
   3. The editor has a bug
   4. The AI suggested a method or class that doesn't exist in the codebase

10. Which statement about how inline AI handles code outside the currently open file is correct?

    1. It cannot access any code outside the current tab without explicit context
    2. It can see files explicitly added to the editor's workspace
    3. It has access to the entire project by default
    4. It can only see code you've explicitly pasted or referenced in comments

11. In what way does writing a detailed comment above code help inline AI produce better suggestions?

    1. Comments are ignored by inline AI
    2. The AI only reads comments, not the actual code
    3. Comments slow down the AI
    4. The AI uses the comment to understand your intent and generate more targeted completions

12. A student is writing a series of unit tests that all follow the same structure. How can inline AI best help?

    1. By completing each subsequent test based on the pattern established in previous tests
    2. By rewriting all tests to use a different testing framework
    3. By explaining what each test does
    4. By generating mock data for all tests at once

13. What should a developer do after accepting an inline AI suggestion, before adding those changes to version control?

    1. Run or compile the code to verify it works
    2. Share it with a teammate first
    3. Delete the file and start over
    4. Take a screenshot of the suggestion

14. Which of these is a key advantage of inline AI tab completion over chat-based AI for certain tasks?

    1. It provides suggestions instantly without waiting for a response
    2. It has better knowledge of your entire codebase
    3. It can think about the entire application's architecture
    4. It can refactor code automatically

15. A developer wants to create a new function that doesn't exist yet. Should they use inline AI tab completion?

    1. No, inline AI can only complete existing code patterns, not invent entirely new functions from scratch
    2. Yes, but only if they first open a different file
    3. Yes, it will always create exactly the function they need
    4. No, but they should use chat instead to reason about the new function