In this article
Explain an AI-assisted repair through the requirement, the counterexample, the choice, and the verification. This original booking exercise shows how to make those decisions visible during an interview that explicitly permits AI assistance.
State the decision before asking for code
An interviewer needs enough context to understand why you accept a suggestion. Reading the assistant's response aloud does not supply that context. Start with the behavior you intend to preserve, then identify the uncertainty that could change your implementation. This gives your next question a purpose and makes it easier to recognize an answer that changes the requirements.
Use this original illustrative exercise only in an assessment that explicitly permits the assistant and the material you plan to share. The dialogue is invented for practice, not a transcript or an employer rubric. Suppose bookings are integer minute offsets within one day. Each has a start smaller than its end. The room becomes available at the ending minute, so 09:00–09:30 and 09:30–10:00 can share it.
Candidate: “I am treating the end as excluded. Two bookings may touch at that boundary. I will confirm that assumption before choosing the comparison.” That sentence exposes a consequential decision without narrating every keystroke.
Demonstrate the boundary the suggestion gets wrong
Imagine the assistant proposes the function below. It looks symmetric and handles many obvious collisions. Give it adjacent intervals, however, and it declares a conflict. Python distinguishes strict comparisons from comparisons that include equality; the language reference supplies those operator semantics, while the scheduling requirement determines which one belongs here. Python language reference: comparisons
Candidate: “For the first comparison, 540 is at most 600. For the second, 570 is at most 570. Both are true, so this suggestion rejects adjacent bookings. Our agreed example says they are allowed.” You have connected an input, a branch, and a consequence. Someone following along can check the reasoning without trusting your opinion of the generated code.
Run the assertion unchanged. Its failure establishes this specific disagreement. It does not yet establish the best replacement, and a failure caused by an import or syntax problem would not demonstrate the scheduling defect.
def overlaps_proposed(a, b):
return a[0] <= b[1] and b[0] <= a[1]
assert overlaps_proposed((540, 570), (570, 600)) is False
Explain why the smaller repair fits the contract
The next decision is about representation. An assistant might suggest subtracting one minute from each end, adding a special adjacency branch, or changing the comparisons. Discuss what each option assumes. Subtraction couples the logic to a one-minute unit. A special branch increases the number of paths to inspect. Strict comparisons express the already agreed rule directly for valid intervals.
Candidate: “I will use strict comparisons because touching endpoints do not share occupied time. I will keep the interval representation unchanged. Invalid intervals remain the caller's responsibility in this exercise.” This is a reasoned choice, not a claim that the shortest patch always wins.
The revised expression is symmetric in the two bookings. That observation suggests a useful follow-up check with arguments reversed, but symmetry alone cannot prove correctness. The proposed function is also symmetric and still fails the adjacency requirement. Connect every appealing property to the behavior it actually establishes.
def overlaps(a, b):
return a[0] < b[1] and b[0] < a[1]
Show independent expectations instead of confidence
Select the expected outcomes before asking the assistant to write assertions. Adjacent intervals should be allowed; a one-minute intersection should conflict; containment should conflict; separated intervals should be allowed. Equal valid intervals also conflict. These are different reasons to exercise the function, even when several happen to visit the same expression.
Paste the repair above the following tests and run the file with Python. The standard unittest library provides equality checks and subtests, allowing a failed example to retain its named case in the report. Python unittest documentation The expected booleans below are literal answers from the requirement; they are not calculated by a second copy of the overlap formula.
Candidate: “These cases support the boundary and containment behavior. I also run each in reverse order. I have not tested invalid intervals or concurrent booking creation.” That closing limit matters: a correct overlap helper does not make the application's read-then-write operation atomic.
import unittest
class BookingTests(unittest.TestCase):
def test_contract(self):
cases = [
("adjacent", (540, 570), (570, 600), False),
("one minute", (540, 571), (570, 600), True),
("contained", (540, 600), (555, 570), True),
("separate", (540, 570), (600, 630), False),
("equal", (540, 570), (540, 570), True),
]
for name, a, b, expected in cases:
with self.subTest(case=name):
self.assertEqual(overlaps(a, b), expected)
self.assertEqual(overlaps(b, a), expected)
if __name__ == "__main__":
unittest.main()
Use a follow-up question to expose your assumptions
Interviewer: “What about an empty booking from 570 to 570?” Candidate: “The current contract rejects it before this helper. If this function must accept arbitrary inputs, I would add validation and agree on its error behavior first.” This response distinguishes a limitation from an accidental promise. Do not invent a validation layer if you have not inspected one in the actual repository.
Interviewer: “Could the tests share your mistake?” Candidate: “Yes. I chose their expected answers from the scheduling examples. I can restore the inclusive comparisons and confirm the adjacency case fails again.” Running that temporary mutation supplies evidence that the suite notices the original defect. Restore the repair before finishing.
Keep the result precise. A unittest failure means an asserted expectation was violated; it does not establish that all unstated requirements are covered. Python unittest documentation If the interviewer changes the rule to require cleanup time, revise the examples and contract before modifying the code.
Reserve explanation for choices that change the result
Continuous commentary can make it difficult to inspect code. Explain at decision points: when you settle a requirement, discover a counterexample, reject an alternative, or obtain a test result. During a short implementation step, a brief statement of intent is enough. Pause for the interviewer to challenge an assumption before it spreads into several files.
A useful assistant request is specific: “Review this overlap predicate for valid intervals whose end is excluded. Explain the adjacent case. Suggest a focused change without introducing rounding, date parsing, or a new representation.” That request gives the model a bounded job while leaving acceptance with you.
Finish by reviewing the actual diff and reporting what ran. Explain that the comparison changed, the adjacency regression now passes, and validation or simultaneous reservations require separate work. Avoid describing a proposed command as a completed check. The explanation should follow evidence you can reproduce.
Common questions about explaining AI-assisted repairs
Should I explain every prompt? Explain prompts that influence the requirement, the implementation choice, or your verification. A transcript of routine retries is less useful than a clear account of which suggestion you accepted and why.
What if the assistant supplies the right answer immediately? You still need to establish the contract and verify it. Walk through a boundary example and inspect relevant callers. Correct generated text does not remove the need for your engineering judgment.
What if there is little time? Prioritize one concrete failure, a justified repair, and a small set of independent checks. State what remains unverified. Practice the exercise again with a different boundary rule so that your explanation reflects the requirement instead of a memorized script.
Sources & editorial notes
This article was authored with AI using primary-source research and an automated technical review. It has not been reviewed by a human. Code examples are illustrative; run and verify them in your own environment.
- Python language reference: comparisons
Defines strict and inclusive comparison operators used in the booking predicate. Retrieved October 20, 2026; evergreen documentation, not a new announcement.
- Python unittest documentation
Documents assertions, subtests, and running the self-contained verification example. Retrieved October 20, 2026; evergreen documentation, not a new announcement.
Put the reading into practice
Work through an existing repository, review AI suggestions, and test the decisions behind your changes.
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