I went straight to the data model and kind of forgot to clarify requirements first, which I noticed about five minutes in.
Start by clarifying requirements and scale, then propose a data model that supports hierarchical tasks (e.g., adjacency list or closure table) and discuss trade-offs. Outline core APIs and system components, and address challenges like recursive queries, concurrency, and performance.
Pro tip: Demonstrate maturity by proactively discussing how to handle task deletion or reassignment when a parent task changes, and how to prevent cycles in the hierarchy.
Ask about scale, read/write patterns, depth of nesting, and whether tasks can have multiple parents. This shapes your design choices.
Propose a schema for tasks and relationships. Compare adjacency list, closure table, and nested sets, highlighting trade-offs in query complexity and write performance.
Define core operations: create task, add subtask, move task, get task tree, and update status. Consider how to handle recursive operations efficiently.
Outline services (e.g., task service, hierarchy service), storage (SQL vs NoSQL), and caching. Discuss how to scale reads and writes.
Discuss concurrency (e.g., moving subtasks while updating parent), consistency, and performance optimizations like lazy loading or materialized paths.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.