AI for Design Doc Review

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-ai-coding-AI-and-design-doc-review-creators

1. Which of the following is an example of AI surfacing design considerations that a document might miss?

   1. AI replaces senior engineers on the review team
   2. AI automatically approves the design document without review
   3. AI writes the entire design document for the engineers
   4. AI flags that the design does not address error handling for network failures

2. What capability does AI provide in generating questions for reviewers during design doc review?

   1. AI decides which reviewers should review which documents
   2. AI automatically accepts any design that generates questions
   3. AI predicts what a thorough reviewer would ask and surfaces those questions proactively
   4. AI eliminates the need for any human reviewers

3. How can AI help compare a new design document to prior decisions?

   1. AI decides which past projects are worth remembering
   2. AI analyzes patterns across similar past projects and highlights relevant precedents
   3. AI replaces the need to document design decisions
   4. AI deletes outdated design documents automatically

4. A design document proposes a new database schema. How might AI assist the review process in this scenario?

   1. AI could suggest performance considerations or scaling concerns the author did not address
   2. AI could replace the need for a database entirely
   3. AI could automatically implement the schema in production
   4. AI could approve the schema without any human review

5. Why does the back-and-forth of substantive design discussion remain essential despite AI assistance?

   1. AI systems cannot hold conversations with people
   2. Design decisions involve tradeoffs that require human negotiation and reasoning
   3. Substantive discussions have been fully automated
   4. Back-and-forth is too slow for modern development

6. When an AI system flags 15 potential issues in a design document, what should happen next?

   1. The AI system is turned off to save time
   2. Senior engineers evaluate which issues warrant discussion and which are false positives
   3. All AI-flagged issues are automatically fixed without human review
   4. The design is rejected until all issues are resolved by AI

7. A junior engineer writes a design document and receives AI-generated feedback suggesting they consider caching. What does this illustrate?

   1. AI automatically approving the design
   2. AI writing the design document for the engineer
   3. AI surfacing a design consideration the doc may have missed
   4. AI replacing the need for senior engineer review

8. What is lost if an organization attempts to fully automate design doc review using AI?

   1. The requirement for multiple engineers
   2. The need for any documentation at all
   3. The substantive human discussion that refines designs through debate and tradeoff analysis
   4. The ability to write design documents quickly

9. An AI tool analyzes a new microservices design and finds a similar architecture used two years ago. What value does this provide?

   1. The tool can surface lessons learned from that prior implementation
   2. The tool deletes the new design document
   3. The tool proves the new design is perfect
   4. The tool automatically reuses the old design unchanged

10. Which statement is most consistent with the material?

    1. Experts agree that no one should think about this issue.
    2. Design doc review quality determines project success; AI augments without replacing senior judgment.
    3. The topic has no bearing on day-to-day decisions.
    4. Every claim about this subject has been proven wrong.

11. Which guidance is highlighted as 'Design doc review AI'?

    1. Always agree with the first answer the model gives, no matter what.
    2. Design AI-augmented design doc review. Cover: (1) consideration surfacing, (2) reviewer question generation, (3) prior decision comparison, (4) senior authority preservation, (5) integration with review process, (6) quality measurement.
    3. Skip every safeguard so things move faster.
    4. Treat AI output as flawless and never review it.

12. Which statement best summarizes "AI for Design Doc Review"?

    1. It says the topic is too dangerous to discuss with beginners.
    2. Design doc review is critical but bottlenecked by senior engineer time. AI augments review for faster, deeper feedback.
    3. It argues that the topic is irrelevant outside academic settings.
    4. It claims the subject can be safely ignored by everyday users.

13. Which captures a genuine tradeoff to weigh when applying these ideas?

    1. Convenience and depth are guaranteed to grow together.
    2. There is never any tradeoff between speed and learning.
    3. Speed always damages a project beyond repair.
    4. Speed and convenience can come at the cost of depth, ownership, or skill-building.

14. What should you do with an AI-generated draft before using it?

    1. Read it carefully, check facts, and decide what (if anything) to keep.
    2. Forward it to a friend without reading it yourself.
    3. Delete the entire response and start over from scratch every time.
    4. Submit it untouched and assume everything is correct.

15. Which habit is the biggest pitfall when applying these ideas?

    1. Comparing answers from more than one source.
    2. Skipping review and trusting the first output without checking it.
    3. Asking for examples to make a concept clearer.
    4. Pausing to verify results before acting on them.