A practice prompt we wrote. No company or candidate report names it, so it carries no company tag.

How to answer

The question asks for a decision, so the answer has to show something you built differently because of a risk. Cohere’s Agentic Platform posting asks for evaluation frameworks that measure safety alongside accuracy and latency. Source 1Forward Deployed Engineer, Agentic PlatformPublisherCohere (Ashby job board)Source typecompany job posting In a Blind thread about Anthropic Applied AI interviews, one commenter advised, in September 2026, having good stories ready about AI safety. Source 2Anthropic Applied AI interviewsPublisherBlindSource typecandidate report on Blind

  1. The system and who could be hurt, in two sentences. Users, third parties, the customer’s business. Say what the system could read and what it could do.
  2. The risk as a path. Who does what, what the model then does, and what harm lands on whom. “An email from a stranger gets another tenant’s balance into a reply” is a risk; “data leakage” is a category.
  3. How you knew. An adversarial test set, an evaluation, a near miss in a pilot. Give the before number.
  4. The design change and its cost. What you removed, narrowed or put behind a human: a tool’s permissions, a scope, an approval step, a deterministic check on the output. Then what it cost in features, automation, time or goodwill, and who objected.
  5. The after number and the residual risk. What you measured once the change was in, what risk remains, and who accepted it.

Get the harm path and the design change into your first few sentences, before the evidence. If the interviewer cuts in early, they should already have both.

The trap is the answer an experienced engineer gives without noticing: “we added guardrails to the system prompt”. An instruction to the model is a request, not a control, and an interviewer who knows prompt injection will ask what happens when an input overrides it. The strong answer takes the ability away from the model where the harm is real.

GlossaryForward deployed engineerA software engineer who builds and ships production systems inside a customer’s problem and environment, accountable to that customer’s outcome.More on Forward deployed engineerGlossaryAgentA system in which a model chooses steps and tool calls to complete a task, within limits the design sets.More on Agent

Follow-ups

What the interviewer may ask next, once your first answer is on the table.

  • How did you know the risk was real and not hypothetical? What did you measure before and after?
  • Who argued against the change, and what did it cost them?
  • What risk is still there, and who agreed to live with it?

Where answers go wrong

  • Answers with a control that lives in the prompt (“we told the model never to do that”), so nothing in the system’s design changed and the risk is still there.
  • Names the risk as a category (“hallucination”, “bias”, “data leakage”) with no path from a user’s action to a harm.
  • Tells a story where safety cost nothing, which hides the trade-off the question is asking about.

Answer this in two minutes

Write the answer you would say out loud. The clock starts with your first word.

Two minutes

Illustrative answer about a fictional project

The short version: an email assistant I built could have sent one tenant’s balance and move-out date to a stranger who asked nicely. I changed the design so the model could only ever see the sender’s own account, and I took fee waivers away from it.

Learn this in Module 8: Production AI systems, part of the curriculum.