Instead of immediately seeking interviews, founders can build an AI persona of their ideal customer. By feeding it documents and archetypes, they can rapidly query the persona to test value propositions, pricing, and features, compressing months of traditional customer discovery work into days.

To preempt investor objections, founders should use AI to generate a critical investment memo on their own company. Prompting the AI to identify potential reasons for failure reveals weaknesses in the business plan and pitch, allowing founders to address them proactively before the meeting.

After a promising sales call, combat 'happy ears' by feeding your meeting notes into an AI. Ask it to identify the top three reasons the deal might *not* go through. This provides an unbiased third-party analysis, revealing red flags and potential objections you can address proactively.

Using AI to generate a pre-call hypothesis about a prospect's priorities is valuable even when it's wrong. Presenting a thoughtful, albeit incorrect, idea demonstrates research. This prompts the prospect to correct you, immediately opening the door to a deeper conversation about their actual priorities.

The most effective way to use AI in product discovery is not to delegate tasks to it like an "answer machine." Instead, treat it as a "thought partner." Use prompts that explicitly ask it to challenge your assumptions, turning it into a tool for critical thinking rather than a simple content generator.

Move beyond static scripts by using AI for dynamic sales training. Feed ChatGPT your call transcripts and common objections, then ask it to act as a specific buyer persona. Practice handling its objections in a role-playing chat, and conclude by asking it to provide a score and feedback on your performance.

To assess a product manager's AI skills, integrate AI into your standard hiring process rather than just asking theoretical questions. Expect candidates to use AI tools in take-home case studies and analytical interviews to test for practical application and raise the quality bar.

The most reliable customer insights will soon come from interviewing AI models trained on vast customer datasets. This is because AI can synthesize collective knowledge, while individual customers are often poor at articulating their true needs or answering questions effectively.

The best use for AI-generated customer personas is for early-stage concept validation, not initial need-finding. Use them to quickly screen many potential solutions before validating the most promising ones with real people. This speeds up innovation and keeps ideas confidential from competitors.