Frame your interaction with AI as if you're onboarding a new employee. Providing deep context, clear expectations, and even a mental "salary" forces you to take the task seriously, leading to vastly superior outputs compared to casual prompting.

Don't treat AI as an omniscient expert. Instead, view it as an intern: provide clear, detailed instructions, show examples of the desired output, and always review the results critically. You wouldn't let an intern's work go straight to the board, and you shouldn't with AI either.

Generative AI, like a junior employee, is eager to please and will rush to a final deliverable without sufficient context. Leaders must manage this by iteratively providing information and explicitly stopping the AI from generating the final output prematurely, preventing low-quality "slop".

As AI generates more output, the risk of "AI slop"—low-quality, unverified work—increases. Zapier's internal mantra addresses this head-on. It frames AI as a tool for delegation, but emphasizes that the human user remains fully accountable for the final quality, judgment, and accuracy of the work product.

The primary issue with low-effort AI-generated work is not its poor quality, but how it transfers the cognitive burden of correction and completion to the recipient. This 'masquerades' as finished work but creates interpersonal friction and hidden rework, fundamentally shifting the responsibility for the task's success.

Treat your AI like a brilliant intern who has raw talent but lacks experience and memory. This mental model encourages providing clear instructions and assuming best intentions while being prepared to constantly remind it of past decisions and project constraints, preventing it from making repeated, simple mistakes.

Don't blindly trust AI. The correct mental model is to view it as a super-smart intern fresh out of school. It has vast knowledge but no real-world experience, so its work requires constant verification, code reviews, and a human-in-the-loop process to catch errors.

Blindly applying AI to every task results in low-quality, untrustworthy output ("slop"). The optimal approach involves using AI as an accelerator while retaining human oversight for prompting, verification, and critical judgment. Over-reliance on the AI shortcut diminishes quality and trust.

When employees substitute generic AI-generated content for their own critical thinking, it lowers the overall quality of work. It is incumbent on leaders to identify this "AI slop," call it out, and push their teams to articulate what they actually think, thereby maintaining a high standard for originality.