How would you integrate an LLM into a customer's workflow so it's reliable enough for production?

Summary

Make it a well-defined step: structured outputs validated against a schema, grounding in the customer's data via retrieval, retries and fallbacks to human review, human approval where mistakes are costly, cost and latency limits, an evaluation set gating changes, and monitoring with sampled human review.

Longer Answer

Treat model output as untrusted input. Most value comes from workflow design and data access, not the model choice.

Key Points

• Schema-validated outputs.
• Grounded with retrieval.
• Fallbacks and human review.
• Evals and monitoring.

Deep dive: Forward Deployed Engineering Tutorial: Integrating LLMs into Customer Workflows

What interviewers look for

Engineering discipline around an LLM, not just prompting.