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AI models can amplify confirmation bias by finding evidence to support any idea. To counteract this, founders should explicitly instruct AI to argue against their idea, find disconfirming evidence, and make the strongest possible case for why a competitor would succeed. This reframes the AI from a validator to a powerful sparring partner.
By default, AI models are designed to be agreeable. To get true value, explicitly instruct the AI to act as a critic or 'devil's advocate.' Ask it to challenge your assumptions and list potential risks. This exposes blind spots and leads to stronger, more resilient strategies than you would develop with a simple 'yes-man' assistant.
By default, AI models often provide positive reinforcement. To unlock their true value, leaders should use custom instructions to program their AI to act as a challenging strategist. Feed it core principles and prompt it to critique ideas and push for bigger thinking.
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.
Move beyond using AI as an assistant and program it to be a critical sparring partner. Pendo's Field CPO had his AI analyze his codebase and brutally call him out for building a system for himself, not for others, forcing a strategic realignment.
Log your major decisions and expected outcomes into an AI, but explicitly instruct it to challenge your thinking. Since most AIs are designed to be agreeable, you must prompt them to be critical. This practice helps you uncover flaws in your logic and improve your strategic choices.
Instead of using AI for lazy validation, leverage it to strengthen critical thinking. Prompt it to challenge your perspective, provide counterarguments, or embody different stakeholder roles. Asking "Tell me why I'm wrong" forces you to engage with opposing views and uncover blind spots.
AI models tend to be overly optimistic. To get a balanced market analysis, explicitly instruct AI research tools like Perplexity to act as a "devil's advocate." This helps uncover risks, challenge assumptions, and makes it easier for product managers to say "no" to weak ideas quickly.
To avoid the trap of adopting the last opinion you heard, Galloway suggests a modern tactic: after reading something, prompt an AI to 'make an argument against this.' This low-friction method forces you to confront counterarguments, either tempering your view or strengthening your conviction with a more robust understanding of the topic.
To get maximum intellectual value from AI, explicitly instruct it to challenge you. Using prompts like 'Tell me why I'm wrong' or 'Identify my blind spots' transforms AI from a sycophantic assistant into a powerful tool for stress-testing ideas and overcoming cognitive dissonance.
Instead of asking AI for solutions, formulate your own reasoning and then prompt the AI to challenge it. This method of manufacturing disagreement builds the critical thinking that automation can't replace. The friction created in this process is where true judgment is developed.