Go beyond simply asking AI for answers. Use "reverse prompting" by instructing the AI to ask you clarifying questions about your goal. This forces you to think more deeply about your problem and provides the AI with better context, ultimately yielding superior results.

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.

Instead of trying to craft a perfect, detailed prompt, Andrew Wilkinson tells the AI his high-level goal and instructs it to "ask me a shitload of questions to determine your prompt." The AI then conducts a 5-10 minute interview, gathering all necessary context to produce a superior result.

Instead of only giving instructions, ask ChatGPT to first ask you questions about your goal. This leverages the AI's knowledge of what information it needs to produce the best possible, most tailored output for your specific request.

AI output quality suffers from incorrect assumptions. By prompting the AI to use its 'ask user questions' tool, it generates a custom UI to seek clarification on ambiguities. This shifts the burden of providing perfect context from the user to a collaborative dialogue with the AI.

Effective AI prompting involves providing a detailed narrative of the situation, user, and goals. This forces the AI to ask clarifying questions, signaling a deeper understanding and leading to more relevant answers compared to a simple, direct command.