Design LLM eval platform (Braintrust/LangSmith) + DSA review

Interview questions to prep

1. Pick between Dijkstra, Bellman-Ford, Floyd-Warshall, MST (Prim/Kruskal), or topo sort — defend the choice.
2. What does this problem assume about edge weights (non-negative? integer? bounded?) — and what breaks if those don't hold?
3. Walk me through complexity in V and E, and the data-structure choice (heap vs Fibonacci heap vs array).

Interview questions to prep

1. Walk me through designing an internal LLM eval platform.
2. What dimensions would you slice eval results by?

Interview questions to prep

1. How would you continuously evaluate a production LLM agent on real traffic without leaking PII?
2. How do you keep eval datasets fresh as user behavior shifts — what's the refresh cadence?