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The CRIT (Context, Role, Interview, Task) prompt framework transforms AI from a simple tool into a thought partner. The key is the 'Interview' step, where you instruct AI to ask you probing questions, uncovering blind spots and elevating your strategic thinking to a top 1% level.

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To unlock AI's value for strategy, provide detailed prompts with context, competitors, and goals. This elevates it from a simple content generator to a thinking partner, yielding deeper, more nuanced answers than basic, search-like queries.

Move beyond using AI for data consolidation and generation by treating it as a tough critic. Prompt it with questions like, "What have I missed?" or "If you were a top consultant, what would you have spotted?" This reframes the AI as a thought partner, forcing it to challenge your assumptions and uncover strategic blind spots.

Instead of asking AI for answers, command it to ask you questions. Use the "Context, Role, Interview, Task" (CRIT) framework to turn AI into a thought partner. The "Interview" step, where AI probes for deeper context, is the key to generating non-obvious, high-value strategies.

Instead of simply commanding an AI, a team first instructed it to ask clarifying questions about their company's mission and selection criteria for podcast guests. This "interview" step forced the AI to understand deep context before generating outputs, leading to a much more effective and customized database of ideas.

Go beyond simple instruction. Explicitly prompt your AI to use tools like `ask_user_question` to push your thinking, question your goals, and suggest alternative angles. This transforms the AI from a simple executor into a powerful strategic thinking partner.

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.

Go beyond using AI for summarization by treating it as a strategic thought partner. After developing a plan, ask the AI to 'pressure test' it, 'tell you where you're wrong,' or identify blind spots to refine your thinking before presenting it to stakeholders.

Instead of providing a detailed but potentially incomplete prompt, ask the AI model to interview you about your goal. This meta-prompting technique forces clarification and helps uncover "unknown unknowns" you hadn't considered, leading to a much better final output.

Instead of asking an AI to solve a problem directly, start by dumping your entire idea into the tool. Then, prompt the AI to act as an interviewer, asking clarifying questions. This iterative process helps refine the concept and uncovers hidden requirements, turning the AI into a true brainstorming partner rather than just a code generator.

Instead of just giving AI a task, command it to interview you first. By having the AI ask clarifying questions about assumptions, context, and potential gaps, you can surface your own unknown unknowns and provide the necessary context for a high-quality output.