← Openai Interview Insights

Openai·Frontend Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Frontend coding round at OpenAI where I had to build a simplified ChatGPT-style UI from scratch, using a reference video as the spec. Finished faster than expected and spent the back half of the session just talking with the interviewer.

Questions Asked (1)

Q1

Build a simplified chat UI with an input box and submit button that renders streaming text responses from an AI backend, using a provided reference video as a visual guide.

API & IntegrationsSystem DesignTechnical Trade-offs
Author's notes

Knocked this out in about 35 minutes which surprised me a bit.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then outline a component architecture that separates concerns: input handling, message state, and streaming logic. Focus on the streaming implementation using fetch with ReadableStream or EventSource, and discuss trade-offs like error handling, performance, and UX details such as auto-scroll and loading indicators.

Pro tip: Demonstrate awareness of real-world streaming challenges: mention handling partial chunks, aborting requests, and ensuring the UI remains responsive. Also, reference the provided video to align with expected visual behavior, showing attention to detail.

1. Clarify Requirements and Constraints

Ask about expected message format, streaming protocol (e.g., SSE, WebSockets), error handling, and any design constraints from the reference video. Confirm whether to use a specific framework or vanilla JS.

2. Design Component Architecture

Outline a simple component structure: a ChatContainer managing state, an InputBox for user input, and a MessageList rendering messages. Emphasize separation of concerns and reusability.

3. Implement Streaming Logic

Describe how to consume a streaming API using fetch with ReadableStream or EventSource, parsing chunks and updating the UI incrementally. Mention handling backpressure and cancellation.

4. Enhance UX and Error Handling

Discuss auto-scrolling to the latest message, showing a loading indicator, disabling input during streaming, and gracefully handling network errors or aborts.

5. Review and Iterate

Compare the implementation against the reference video, ensuring visual and behavioral alignment. Suggest potential optimizations like debouncing or virtualized lists for long conversations.

Key Points to Mention

  • Use of fetch with ReadableStream or EventSource for streaming responses
  • State management for messages and streaming status (e.g., React useState/useReducer)
  • Handling partial data chunks and updating UI incrementally
  • Error handling and request cancellation (AbortController)
  • Auto-scroll and loading indicators for better UX
  • Trade-offs between SSE, WebSockets, and long-polling for streaming

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