17How do you implement citations and source attribution in a RAG system, and why does it matter?▼mediumGleanMicrosoftCohere2 replies○ sign inCitations turn a RAG answer from 'trust me' into something checkable, and they are a genuine engineering problem. The signal is grounding each claim to a specific passage and verifying the attribution, not tacking a bag of links onto the end.Open full answer →
99When should an agent act without being asked?▼mediumAnthropicOpenAIMicrosoft◆ premiumA proactive agent runs on a trigger, with no human watching at the moment of action. That inverts the risk model, and the interviewer is listening for whether you separate notifying from acting.Open full answer →
118Users do not trust your AI feature. How do you design for trust?▼mediumGoogleMicrosoftGitHub◆ premiumTrust is an interface and reliability problem, not a messaging one, and the goal is not maximum trust. Here is the mechanism list that actually moves it, the recovery path after a public failure, and the metric most teams optimize in the wrong direction.Open full answer →
34How do you communicate an AI system's reliability and limitations to a non-technical stakeholder or customer?▼mediumOpenAIAnthropicGoogle2 replies◆ premiumAI features are probabilistic, yet stakeholders hear 'it works.' Setting honest expectations without draining enthusiasm is a core applied-AI skill. Here is how to frame reliability so trust holds through the first mistake.Open full answer →
35A customer expects the AI to be flawless and magical. How do you manage unrealistic expectations?▼medium★ EssentialSalesforceSierraDecagon1 replies◆ premiumHype primes customers to expect a system that reads minds and never fails. Resetting that without losing the deal is an applied-AI skill interviewers probe head-on. Here is the move.Open full answer →
37Your AI system made a visible mistake that affected a customer. How did you handle it and rebuild trust?▼mediumSierraDecagonSalesforce2 replies◆ premiumAI features break in public, sometimes embarrassingly. How you respond to the customer, not only the bug, is what this question actually tests. Here is the recovery that rebuilds trust.Open full answer →
41A customer's team is nervous about adopting your AI feature. How do you build trust and drive adoption?▼mediumSalesforceGleanPalantir2 replies◆ premiumThe model can be excellent and still fail if the people who must use it do not trust it. Adoption is change management, not a slicker demo. Here is how forward-deployed engineers actually earn it.Open full answer →
42Tell me about a time you handled a difficult or angry customer. How did you turn it around?▼mediumPalantirSierraDecagon1 replies◆ premiumAn angry customer tests composure and ownership, not empathy alone. Interviewers want to watch you de-escalate, fix the real problem, and rebuild trust. Here is the arc that scores.Open full answer →
54A customer's security team raises objections that block your deployment. How do you handle it?▼mediumPalantirAWSMicrosoft2 replies◆ premiumSecurity and compliance teams are gatekeepers, not adversaries. Interviewers look for you to bring them in early, satisfy real requirements, and turn a blocker into an ally. Here is the approach.Open full answer →
55How do you tell a customer no without damaging the relationship?▼mediumSalesforcePalantirSierra1 replies◆ premiumTelling a customer no is a relationship skill: shield them from a bad outcome while keeping their trust. Interviewers look for the reason, the alternative, and the framing. Here is the move.Open full answer →