Amazon AI-Assisted Coding OA Guide 2026: Repository Bugs, AI Prompts, and Hidden Tests

An unfamiliar repository is open, several tests are failing, and an AI assistant is waiting for instructions. The hard part is not asking AI to "fix the code." It is understanding the system well enough to decide what to ask, whether the answer is correct, and what the hidden tests may still expose.

That is the emerging challenge described in multiple 2026 Amazon candidate reports. Amazon has not published one universal AI-assisted OA format, so this guide separates official guidance from reported experiences and gives you a preparation method that remains useful when the exact timer, repository, or number of bugs changes.

Start with PracHub's real Amazon interview questions, especially the current software engineering fundamentals and coding reports. Then use the workflow below to turn those questions into repository-level debugging practice.

The strongest candidate stays in control of the diagnosis, the generated diff, and the final evidence.

Quick Verdict

Treat the Amazon AI-assisted coding task as a debugging assessment with an AI tool, not a prompt-writing contest. Recent candidate reports describe an unfamiliar codebase, broken behaviors, an embedded assistant, and visible or hidden tests. The exact structure appears to vary by role and location.

Your best loop is: reproduce the failure, trace the code path, form a hypothesis, ask one bounded question, inspect the diff, run tests, and verify the contract yourself.

Use only tools that the assessment explicitly provides or permits. Amazon's current university OA guidance says browser activity may be logged and warns candidates against copy-paste behavior; the instructions in your invitation and test environment are the final authority.

What Is the Amazon AI-Assisted Coding OA?

Amazon's official SDE assessment pages still describe role-dependent coding assessments and tell candidates to check their invitation for the exact structure. The university page says formats can differ by country, while the SDE II page describes a more traditional two-question coding challenge.

Separately, multiple 2026 candidate reports describe a newer repository task with a built-in AI assistant. Reports commonly mention fixing several bugs in an existing application and passing a test suite. Some candidates received a traditional algorithm question plus the repository task; others reported different sequencing, timers, and test counts.

Practical conclusion: prepare for the reported repository format, but do not memorize one candidate's numbers. Read your invitation as the test specification.

How It Differs From a Traditional DSA Question

A normal coding question gives you a compact contract and asks you to design an algorithm. A repository task gives you a partially working system and asks you to recover the contract before making a safe change.

Do not abandon algorithms. Candidate reports suggest the new task can appear alongside conventional coding, and later Amazon interviews still test coding fundamentals. Use PracHub's Amazon Software Engineer coding questions to keep that lane active.

What the Task Is Likely Measuring

Amazon has not published a scoring rubric for this reported format. Based on the task design, official emphasis on robust and well-tested code, and repeated candidate descriptions, the following skills are reasonable preparation targets rather than confirmed score weights.

The common thread is engineering control. AI may accelerate exploration, but you still own the diagnosis and the submitted code.

The Seven-Step Repository Debugging Loop

Keep each cycle small enough that you can connect evidence, change, and result.

1. Read the Contract Before the Implementation

Scan the task description, README, test commands, project structure, and visible tests. Write down the expected behavior in one sentence. A failing test is evidence; it is not always the complete requirement.

2. Reproduce One Failure

Run the smallest relevant test or action. Capture the exact assertion, exception, status code, or state mismatch. If everything is failing, choose one representative path instead of asking the assistant to repair the entire repository.

3. Trace the Execution Path

Follow the request or function call from entry point to data access. Search for the failing symbol, related model fields, and neighboring tests. Sketch a short path such as route -> controller -> service -> repository.

4. State a Hypothesis

Write what you think is wrong and what observation would disprove it. This prevents random edits and gives the AI assistant a bounded investigation.

5. Prompt for One Job

Ask the assistant to inspect a specific path, explain a condition, or propose the smallest patch. Include the requirement, observed failure, relevant files, and constraints. Do not ask it to change tests merely to make them green.

6. Review the Diff

Check every changed line. Look for altered public behavior, swallowed errors, duplicated logic, unrelated refactors, invented APIs, or broad exception handling. Revert anything you cannot defend.

7. Verify Narrowly, Then Broadly

Re-run the original failure first. Then run the surrounding tests and, if time permits, the full suite. Finally, test one boundary that was not visible in the samples.

For more practice with this exact mode of thinking, use PracHub's existing codebase interview guide.

How to Write Better AI Prompts

A useful prompt reduces uncertainty without surrendering judgment. A weak prompt hides your reasoning and invites a large, hard-to-review patch.

A repeatable prompt format is context + expected behavior + observed evidence + scope + requested action + constraints. After the response, inspect the code yourself. A polished explanation is not proof.

Worked Example: A Bug the AI Can Easily Misdiagnose

Imagine a service that funds a loan. The visible test checks a normal transfer, but a hidden test may try a zero amount, an amount above the remaining loan balance, or a write that succeeds for one record and fails for the other.

async function fundLoan(userId: string, loanId: string, amount: number) {
  const user = await users.find(userId);
  const loan = await loans.find(loanId);

  if (user.balance < amount) throw new Error("insufficient balance");

  user.balance -= amount;
  loan.funded += amount;
  await users.save(user);
  await loans.save(loan);
}

The obvious check is present, but the contract is incomplete. A strong candidate asks: Can amount be zero or negative? Can funding exceed the loan's remaining amount? What happens when either entity is missing? Must the two writes be atomic?

A bounded prompt might be: "The funding service passes the happy path but the contract requires a positive amount, no overfunding, and no partial state update. Inspect this method and its repository API. Propose the smallest change that enforces those invariants without changing tests."

Then verify the proposed patch against amount = 0, a negative amount, exactly the remaining balance, one unit above it, insufficient user funds, missing entities, and a simulated persistence failure. The assistant can suggest code; only your tests establish confidence.

What Hidden Tests Usually Probe

Translate every requirement into at least one normal case, boundary, and failure case.

Hidden tests are usually not riddles. They encode requirements and engineering invariants that the visible examples do not fully cover. PracHub's guide to coding assessment hidden test cases provides a broader boundary checklist.

Five Mistakes That Waste the Most Time

Prompting before reproducing. Without the actual failure, the assistant guesses from surface patterns.

Changing too much at once. A multi-file refactor makes it harder to identify which edit fixed the bug and which introduced a regression.

Editing the tests to match the code. Unless the task explicitly says a test is wrong, the tests and written contract are evidence to satisfy, not obstacles to remove.

Trusting green visible tests. A happy-path suite may still miss authorization, rollback, boundary, and idempotency failures.

Using unapproved external tools. Practice with any lawful tool you prefer, but during the live OA use only resources allowed by Amazon and the assessment provider. Do not paste private assessment content into outside services.

A Seven-Day Preparation Plan

Use PracHub's Amazon question hub for the diagnostic and algorithm practice. For the later behavioral stage, pair technical preparation with Amazon Leadership Principles questions and the Amazon OA Work Simulation guide.

Practice with real questions from PracHub

These are real Amazon question-bank records, not a prediction of your exact assessment. We prioritize source reports that mention an OA, then use PracHub's stored Technical Screen, Onsite, and Take-home rounds. The table keeps the stored round visible so the evidence is not relabeled.

What the prompts actually ask

Q1. Highest Average-Salary Team in an Org Chart
Bank evidence: Amazon, Technical Screen, Medium. Highest Average-Salary Team in an Org Chart A company's reporting structure is a single hierarchy. Every employee has a unique integer id, a name, an integer salary, and a managerid — the id of the person they report to. Exactly one employee (the CEO) has managerid = null, meaning they have no manager.

Q2. Merge Overlapping Time Ranges
Bank evidence: Amazon, Technical Screen, Medium. Merge Overlapping Time Ranges You are building the scheduling backend for a shared conference room. Each reservation that has ever been placed is recorded as a pair [start, end] of integer timestamps (epoch seconds), where start <= end.

Q3. Caesar Cipher with Translation-Table Optimization
Bank evidence: Amazon, Technical Screen, Medium. Implement a Caesar cipher. Given a string text and an integer shift, return a new string in which every alphabetic character is rotated forward by shift positions within its own case, wrapping around the alphabet; all non-alphabetic characters are left unchanged.

Q4. Detect and Break a Cycle in a Singly Linked List
Bank evidence: Amazon, Technical Screen, Medium. You are given the head of a singly linked list. The list may or may not contain a cycle: somewhere in the list, one node's next pointer may point back to an earlier node, forming a loop. Do two things: 1. Detect whether the list contains a cycle. 2.

Run the set like an assessment

1. Read all four prompts first. Give each a difficulty estimate and choose an order before coding.
2. Hide the solution. Write the invariant, complexity target, and three edge cases before opening the editor.
3. Use one timer. Preserve five minutes at the end for boundary, tie, scale, and output-format tests.
4. Log the failure mode. Record the broken invariant or missed edge case, not merely the question title.

Amazon AI-Assisted Coding OA FAQ

Is the AI-assisted repository task now on every Amazon SDE OA?

No public Amazon page confirms that. Multiple 2026 candidates report receiving it, including candidates for SDE I, graduate, intern, and some SDE II processes, but the format varies. Follow the structure stated in your invitation.

How many bugs and hidden tests are there?

Candidate reports mention different bug and test counts. Do not prepare around one number. Train a repeatable debug-and-verify loop that works whether the repository contains two defects or several.

Is the built-in assistant Amazon Q?

Do not assume so. Amazon has public documentation for Amazon Q Developer, but that does not establish the identity or capabilities of an assessment's embedded assistant. Use the interface and help text presented in your assessment.

Can I use ChatGPT, Claude, or another external AI during the OA?

Only if the assessment instructions explicitly allow it. Amazon's university OA guidance says browser usage may be logged and warns against copy-paste behavior. The safe rule is to use only the built-in assistant and resources expressly permitted for your test.

What if the AI produces a patch that passes visible tests?

Review the diff and test the contract yourself. Check invalid input, boundaries, persistence, authorization, retries, and adjacent behavior. You are responsible for the submitted implementation, even when a tool generated part of it.

Does passing every test guarantee an interview?

Amazon does not publish a universal cutoff or weighting for this reported task. Official OA pages describe a broader evaluation that can include coding, problem solving, work styles, and other role-dependent sections. Complete every required section carefully.

Final Takeaway

The 2026 Amazon AI-assisted coding OA changes the interface, not the engineering standard. You still need to understand requirements, navigate unfamiliar code, isolate a defect, make a small defensible change, and prove that it works beyond the happy path.

Practice the two lanes together: use PracHub's Amazon coding questions for algorithm speed, then use current Amazon interview reports and written solutions to train debugging, testing, and full-loop judgment. The goal is not to make AI look capable. It is to show that you remain the engineer in control.

Sources and Further Reading

• Amazon Jobs: Online Assessment Prep for SDE Roles
• Amazon Jobs: SDE II Online Assessment Prep
• Amazon Jobs: Software Development Interview Topics
• Candidate discussion: Amazon SDE I AI-assisted repository format
• Candidate report: SDE I Graduate OA, London, July 2026