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Openai·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
May 2026

Summary

OpenAI Research Engineer system design round, one big question that basically ate the whole session. They took an existing text editor spec and asked you to bolt on real-time collaboration, which sounds scoped until you realize they want the full distributed systems treatment.

Questions Asked (1)

Q1

You're given a text editor that already supports insert/delete operations, undo/redo, and prefix autocomplete with word frequency rankings. How would you extend it to support real-time collaborative editing across multiple clients, where operations can arrive out of order and all clients must eventually converge to the same document state?

System DesignTechnical Trade-offsAlgorithms & Data Structures
Author's notes

This one spiraled fast.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints (e.g., number of clients, latency, offline support). Then propose a CRDT-based approach (e.g., RGA for text) to ensure eventual consistency, explaining how it integrates with existing features like undo/redo and autocomplete. Finally, discuss trade-offs (e.g., CRDT vs OT) and how to handle out-of-order operations and convergence.

Pro tip: Demonstrate awareness of real-world complexities: mention that CRDTs can have metadata overhead and that undo/redo in a collaborative context requires careful design (e.g., selective undo). Also, highlight that autocomplete rankings may need to be eventually consistent or computed locally.

1. Clarify Requirements and Constraints

Ask about expected number of concurrent users, latency requirements, offline support, and whether the editor is peer-to-peer or server-mediated. This shapes the choice of algorithm and architecture.

2. Choose a Consistency Model

Decide between Operational Transformation (OT) and Conflict-free Replicated Data Types (CRDTs). For out-of-order operations and eventual convergence, CRDTs like RGA or Logoot are often simpler to reason about.

3. Design the Data Model and Operations

Represent the document as a sequence of characters with unique identifiers (e.g., timestamps, site IDs). Define insert/delete operations that can be applied in any order and still converge.

4. Integrate with Existing Features

Adapt undo/redo to work with CRDTs (e.g., using selective undo or inverse operations). For autocomplete, either compute rankings locally from the converged document or use a separate eventually consistent service.

5. Address Trade-offs and Edge Cases

Discuss metadata overhead, garbage collection, and performance. Consider network partitions, offline editing, and how to handle conflicts in autocomplete rankings.

Key Points to Mention

  • CRDTs (e.g., RGA, Logoot, Yjs) provide eventual consistency without central coordination.
  • Operational Transformation (OT) requires a central server or complex transformation functions; CRDTs are more suitable for out-of-order operations.
  • Unique identifiers for each character (e.g., (siteID, counter)) enable deterministic ordering.
  • Undo/redo in collaborative editing must be selective and not undo other users' changes.
  • Autocomplete word frequency rankings can be maintained per-client or via a separate eventually consistent store.
  • Trade-offs: CRDTs have higher metadata overhead but simpler convergence; OT has lower overhead but requires central server and complex transforms.

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