13Role-play: a CTO tells you 'we tried GPT last year, it hallucinated all over our data, AI doesn't work.' Respond.▼mediumOpenAIAnthropicScale AI3 replies○ sign inThe most common objection in enterprise AI, and arguing back is the fastest way to fail it. The winning sequence is validate, diagnose, reframe, de-risk. Here's the script.Open full answer →
14An exec asks point-blank: 'Can it be 100% accurate?' Answer without lying, and without losing the deal.▼easyHarveyAnthropicSierra1 replies○ sign inSay 'yes' and you've failed the integrity test; say 'no' flatly and you've failed the deal. The pass is a three-beat answer that turns the question into the reason to buy. Here's the script.Open full answer →
19The customer insists on fine-tuning when RAG clearly fits. They won't budge. Trusted advisor or vendor, what do you do?▼mediumOpenAICohereDatabricks1 replies○ sign inThe defining trusted-advisor dilemma, and both pure compliance and pure stubbornness fail it. The strong move is a sequence: diagnose, recommend in writing, then a test that lets the evidence decide.Open full answer →
23Present your architecture to a mock customer panel, who will interrupt, object, and try to rattle you.▼hardDatabricksSnowflakeGoogle1 replies◆ premiumThe Databricks/Snowflake signature round: the interruptions ARE the interview. Here's how to structure for derailment, the objection-handling loop that scores, and why finishing your deck doesn't matter.Open full answer →
25CISO ambush: 'Where does our data go? Do you train on it? SOC 2? Residency?', all before your first slide.▼hardAnthropicOpenAIGlean1 replies◆ premiumThe security ambush kills more enterprise AI deals than accuracy ever will, and it's pass/fail on precision. Here's the answer stack a strong FDE has memorized, and the one response that ends the meeting.Open full answer →
45Explain to a non-technical CFO why your deployed generative model gives different answers each run, and why that's expected, not a bug.▼easyAnthropicHarveySierra1 replies◆ premiumThe CFO ran the same prompt twice and got two answers, and now thinks the system is broken. The analogy that lands in one sentence, the honest framing that keeps trust, and the exact case where you'd set temperature to zero to make it repeat.Open full answer →
18The customer asks: 'Will you train on our data?' Give the precise answer, and explain zero-data-retention.▼easyOpenAIAnthropicGlean1 replies○ sign inThe most-asked question in every enterprise AI deal, and precision is pass/fail: the contractual answer, what ZDR actually changes, and the retention nuance that separates FDEs from demo engineers.Open full answer →