Telling Claude or ChatGPT to write tests before the function forces you to lock in what 'done' looks like.
7 min · Reviewed 2026
The big idea
Test-driven development means writing the test first, watching it fail, then writing code until it passes. Asking an AI to draft the tests from your description is fast and exposes vague specs immediately — you'll see when the AI invents details you never said.
Some examples
You ask Claude 'write 5 tests for a function that converts USD to EUR' and notice it assumed a fixed rate — so you specify a rates argument.
You tell ChatGPT to write Jest tests for a login form and it asks 'what happens with empty input?' — a case you forgot.
You have Cursor generate Pytest cases for a parser and it covers an edge case (empty string) you'd have shipped broken.
You ask Copilot for tests of a sort function and it includes negative numbers and duplicates.
Try it!
Pick a small function you want to write. Describe it in one paragraph to an AI and ask for 5 tests before any code. Notice which tests surprise you.
End-of-lesson check
8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-builders-aicoding-ai-writes-test-first-r8a8-teen
What is the main idea of "Asking AI to Write the Tests First"?
Telling Claude or ChatGPT to write tests before the function forces you to lock in what 'done' looks like.
Use AI as the final authority for the whole decision
Avoid checking the answer once it sounds polished
Focus only on speed instead of judgment
Which concept is most central to "Asking AI to Write the Tests First"?
test-first
TDD
specs
AI tests
Which use of AI fits this topic best?
Let the AI decide what matters without your review
Use the answer before checking whether it fits the situation
You ask Claude 'write 5 tests for a function that converts USD to EUR' and notice it assumed a fixed rate — so you specify a rates argument.
Use the first answer without checking it
What should a careful learner remember about "The rule"?
Read the AI's tests carefully — every assumption it made is a spec gap you need to close.
Skip the context so the tool can guess faster
Treat the output as private even after sharing it online
Use the answer without checking the source
You want to use AI after this lesson. What is the safest next step?
Act immediately because the AI answer is written clearly
Use the AI answer as a draft, then check it against a reliable source.
Hide uncertainty so the final answer looks cleaner
Use private or sensitive details before checking permission
How should AI output about TDD be treated?
As proof that no other source is needed
As a replacement for context, consent, or expert review
As a draft or helper output that still needs human judgment and verification
As something that becomes correct when it sounds confident
Name one way to verify an AI answer about TDD.
Which action would help you apply "Asking AI to Write the Tests First" responsibly?
Use the tool to avoid thinking through the tradeoff
Keep going even if the output conflicts with a trusted source
Use the first answer without checking it
You tell ChatGPT to write Jest tests for a login form and it asks 'what happens with empty input?' — a case you forgot.
