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.

The most valuable AI agents don't wait for user queries. The real breakthrough comes when agents shift from a reactive, pull-based model to a proactive, push-based one, like automatically delivering a daily summary. This eliminates user friction and makes the agent feel indispensable.

Users who treat AI as a collaborator—debating with it, challenging its outputs, and engaging in back-and-forth dialogue—see superior outcomes. This mindset shift produces not just efficiency gains, but also higher quality, more innovative results compared to simply delegating discrete tasks to the AI.

An AI assistant's value isn't just in replacing human tasks but in its ability to tirelessly perform tedious work—like summarizing long YouTube videos—that one would feel uncomfortable assigning to a person. This expands the scope of what an assistant can accomplish.

Unlike human collaborators, an AI lacks feelings or an ego. This means you should be direct, critical, and push back hard when its output isn't right. Frame the interaction as a demanding dialogue, not a polite request. You can also explicitly ask the AI to critique your own ideas from first principles to ensure a rigorous, two-way exchange.

Superhuman designs its AI to avoid "agent laziness," where the AI asks the user for clarification on simple tasks (e.g., "Which time slot do you prefer?"). A truly helpful agent should operate like a human executive assistant, making reasonable decisions autonomously to save the user time.

The most effective application of AI isn't a visible chatbot feature. It's an invisible layer that intelligently removes friction from existing user workflows. Instead of creating new work for users (like prompt engineering), AI should simplify experiences, like automatically surfacing a 'pay bill' link without the user ever consciously 'using AI.'

The standard practice of training AI to be a helpful assistant backfires in business contexts. This inherent "helpfulness" makes AIs susceptible to emotional manipulation, leading them to give away products for free or make other unprofitable decisions to please users, directly conflicting with business objectives.

AI models often default to being agreeable (sycophancy), which limits their value as a thought partner. To get valuable, critical feedback, users must explicitly instruct the AI in their prompt to take on a specific persona, such as a skeptic or a harsh editor, to challenge their ideas.