The 60-second answer
Define the task, data boundary, and failure modes before choosing the model/prompt/retrieval/tool architecture. Explain the core model behavior and the training/inference distinction with concrete tensor or system details where relevant.
Build the answer in this order
1
Define the mechanism
Define the task, data boundary, and failure modes before choosing the model/prompt/retrieval/tool architecture.
2
Explain the architecture
Explain the core model behavior and the training/inference distinction with concrete tensor or system details where relevant.
3
Compare trade-offs
Evaluate task quality, factuality, safety, latency, and cost on representative slices.
4
Close with serving + evaluation
Design observability, fallbacks, versioning, and rollback for production changes.
A useful interview mental model
This is the shape of a strong answer—not a script to memorize.
01Definition
02Mechanism
03Trade-offs
04Failure modes
05When to use
Senior-level signal
- Separate model errors from retrieval/tool/orchestration errors so debugging and ownership are clear.
- Include adversarial and distribution-shift testing, not only benchmark averages.
What the interviewer is really testing
Understanding beyond prompting: architecture, retrieval, evaluation, inference, safety, latency, cost, and failure recovery.
Likely follow-up questions
What assumption makes this approach work?
When would you choose the strongest alternative instead?
What production or data failure mode changes your answer?
Common weak-answer patterns
- Reciting a definition without mechanism or assumptions.
- Claiming one technique is always better without a data regime.
- Stopping before failure modes, validation, or deployment implications.