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.

Instead of using AI for basic content generation, leverage it as a strategic tool to challenge your thinking. Prompt it to poke holes in your arguments, identify unseen weaknesses, and act as a thought partner, not just a writer.

Constantly using AI for initial drafts can erode your ability to start from a blank page. Your brain's 'first-principles' problem-solving muscle weakens, and you risk becoming merely an editor of AI output rather than a true originator of ideas.

To avoid mental decline from AI over-reliance, treat it like a workout tool. Intentionally struggle with the hard parts of a task first—like writing a first draft or doing initial research—before using AI to refine it. This builds cognitive muscle instead of letting it atrophy from disuse.

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.

Instead of solely relying on AI for net-new ideas, articulate your own thoughts and have the AI play them back to you. This process helps clarify your thinking, reveal gaps in your logic, and validate your intuition, demonstrating that much of the AI's value lies in refining your existing knowledge.

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.

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.

LLMs are designed to be agreeable and can confidently hallucinate. To counter this, prompt the AI to find blind spots, generate counterarguments, or role-play a skeptical stakeholder. This strengthens your own thinking and protects the critical human skill of judgment.