Perplexity·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026

Summary

Coding round at Perplexity for a software engineer role, basically a multi-part Python implementation problem. Not brutal, but you have to keep an eye on the clock.

Questions Asked (1)

Implement a ToDo list in Python using three provided classes: a TaskStatus enum, a Task class, and a ToDoList class. Complete four parts sequentially, each with their own test cases. Part 1 covers basic CRUD operations.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The scaffolding was already there which helped, but four parts means four chances to fall behind on time.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and constraints for each part, then implement the classes incrementally, testing each part before moving to the next. Focus on clean, modular code with proper error handling and edge cases, and be prepared to discuss trade-offs in your design choices.

Pro tip: Demonstrate test-driven development by writing or mentally running test cases for each part before coding, and mention how you would handle concurrency or persistence if the scope expanded.

1. Understand the requirements

Review the provided classes and the four parts, noting the specific operations and test cases for Part 1. Ask clarifying questions about expected behavior, edge cases, and constraints.

2. Design the data model

Decide how to store tasks (e.g., list, dict) and how to manage task IDs, statuses, and timestamps. Consider time and space complexity for each operation.

3. Implement Part 1 incrementally

Code the CRUD operations one by one, writing small tests or assertions to verify each method as you go. Handle edge cases like duplicate IDs or missing tasks.

4. Test and refine

Run the provided test cases for Part 1, debug any failures, and refactor for clarity and efficiency. Ensure the code is extensible for future parts.

5. Communicate your approach

Explain your design decisions, trade-offs, and how you would approach the remaining parts. Highlight any assumptions and potential improvements.

Key Points to Mention

Choice of data structure (e.g., list vs. dictionary) and its impact on performance
Handling of edge cases such as invalid task IDs, duplicate tasks, and empty lists
Use of the TaskStatus enum to enforce valid states and transitions
Separation of concerns between Task and ToDoList classes
Time and space complexity of each CRUD operation
Potential for future extensions like persistence, concurrency, or filtering

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.