While AI tools once gave creators an edge, they now risk producing democratized, undifferentiated output. IBM's AI VP, who grew to 200k followers, now uses AI less. The new edge is spending more time on unique human thinking and using AI only for initial ideation, not final writing.

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.

Relying on AI without applying critical thinking produces "work slop"—outputs that look polished on the surface but lack genuine depth or substance. This can be dangerously misleading and devalues the quality of work by giving a false sense of security.

Unlimited access to AI tools often results in wasted time on frivolous or bad ideas. Similar to how SNL's Lorne Michaels edits creatives to prevent them from 'getting in their own way,' managers must impose constraints and structure to guide AI usage toward valuable outcomes.

The primary danger of AI in product management isn't technical failure but the abdication of critical thinking. Over-relying on AI summaries of user feedback means missing the crucial 'color' and context. Leaders risk losing their direct connection to the customer's voice by outsourcing their thinking to an LLM.

The most significant risk for PMs using AI is not poor prompting but laziness: chaining AI outputs without critical review. This 'garbage in, garbage out' approach removes the human element of taste and intentionality, proving that this level of product management is no longer valuable.

Each generative step in an AI workflow introduces potential degradation or 'lossiness'. Chaining multiple steps together without checks—like asking AI to find a value prop, then an ICP, then write an email—compounds errors and produces generic, ineffective output. It's crucial to be thoughtful about workflow design and human-in-the-loop review.

A concerning trend is using AI to expand brief thoughts into verbose content, which then forces recipients to use AI to summarize it. This creates a wasteful cycle that amplifies digital noise and exhaustion without adding real value, drowning organizations in synthetic content.

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.