Still waiting to take the thing so I can't tell you from experience.
Acknowledge that the AI-assisted coding environment in Amazon's OA is designed to simulate real-world development with AI tools, where both prompting skill and coding ability are essential. Emphasize that the environment tests your ability to leverage AI effectively while still applying core coding principles to verify and integrate solutions. Conclude that success comes from a balanced approach: using AI to accelerate routine tasks but relying on your coding expertise for critical thinking and debugging.
Pro tip: Demonstrate that you understand the AI is a tool, not a crutch—mention that you always review and test AI-generated code for edge cases and efficiency, which shows maturity and aligns with Amazon's high code quality standards.
Briefly describe how the AI-assisted coding environment works, such as an IDE with integrated AI suggestions or a chat interface for code generation. Highlight that it's designed to mimic Amazon's internal AI tools like CodeWhisperer.
Explain that both skills are crucial: prompting helps you get relevant code snippets quickly, while raw coding ability ensures you can understand, modify, and debug the output. Avoid favoring one over the other.
Give a concrete example from your experience where you used AI to generate a function but had to refactor it for performance or correctness, showcasing your coding skills. Alternatively, describe how a well-crafted prompt saved time on boilerplate code.
Tie your answer to Amazon's Leadership Principles, such as 'Learn and Be Curious' for adapting to AI tools and 'Insist on the Highest Standards' for validating AI output. This shows cultural fit.
Conclude that the OA assesses your ability to work synergistically with AI, where prompting is a force multiplier for your coding skills, but ultimately your technical judgment determines success.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Frame your answer around a specific example from the AI-assisted coding round, highlighting how you used prompts to clarify requirements, generate test cases, and debug edge cases. Emphasize a collaborative, iterative approach—treating the AI as a pair programmer rather than a crutch—and tie it back to Amazon's Leadership Principles like Customer Obsession and Learn and Be Curious.
Pro tip: Show that you critically evaluate AI suggestions rather than blindly accepting them; mention a time you rejected an AI-generated solution because it didn't meet performance or correctness standards, and explain how you improved it.
Briefly describe the problem you faced in the AI-assisted coding round and why you chose to use AI assistance.
Give concrete examples of prompts that worked well, such as asking for clarification of ambiguous requirements, generating test cases, or suggesting optimizations.
Clarify whether you approached it as pair programming (iterative dialogue, building on AI suggestions) or primarily for debugging, and justify your choice based on the problem's complexity.
Discuss how you validated AI outputs, caught errors, and ensured the final solution met quality and performance standards.
Summarize what you learned about AI-assisted development and link it to Amazon's Leadership Principles, such as Customer Obsession or Learn and Be Curious.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This is what I'm most curious about going in.
Acknowledge the AI tool's limitations in the OA environment by categorizing them into technical, contextual, and interaction constraints. Then, provide specific examples of tasks it struggled with, such as complex problem-solving or ambiguous requirements, and explain how you adapted your approach to overcome these challenges.
Pro tip: Emphasize that understanding the tool's limitations allowed you to focus on high-value tasks and develop workarounds, demonstrating adaptability and a pragmatic mindset that Amazon values.
Start by recognizing that the AI tool has inherent limitations in the OA environment, showing self-awareness and a balanced perspective.
Group limitations into categories such as technical constraints (e.g., latency, accuracy), contextual constraints (e.g., lack of domain knowledge), and interaction constraints (e.g., difficulty in clarifying ambiguous queries).
Give concrete examples of tasks where the AI struggled, such as debugging complex code, optimizing algorithms, or handling multi-step reasoning problems.
Describe how you adapted your workflow to compensate for these limitations, such as breaking down problems, verifying outputs, or using the AI as a supplementary tool rather than a primary solution.
Conclude by summarizing what you learned about the AI's capabilities and how this experience improved your problem-solving and tool-evaluation skills.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.