Question
You are given a DAG of n tasks (0..n-1) as edges [u, v] meaning task u must complete before task v starts, plus a duration[i] for each task. A task can start only after all its prerequisites finish, and independent tasks run in parallel. Return the minimum total time to finish all tasks (the length of the longest weighted path through the DAG, where a node's weight is its duration). The input is guaranteed acyclic.
min_project_time(n: int, edges: list[list[int]], duration: list[int]) → int[3,[[0,2],[1,2]],[3,2,5]]out8State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
Vibe coding: describe the solution in plain language (or narrate it) and the coach grades your approach. Generating runnable code from your description is coming next.