The AI “Rabbit-Hole’ing” Problem

See if this sounds familiar. You bring a question to your favorite LLM, hoping Gemini or ChatGPT can help you think through a real business or leadership challenge. You write a thoughtful prompt that frames the situation, the context, and what you’re trying to solve. Within seconds, a direction begins to emerge and the outline of a strategy starts to take shape.

It feels impressive, efficient, and energizing. Then the follow-up questions arrive. “Would you like a set of action steps to support this strategy?” “Should we identify the most likely barriers to execution?” “Do you want metrics, timelines, risks, refinements, or alternative approaches?”

Each question feels reasonable. Each response adds value. As the conversation continues, the list grows longer, the ideas multiply, and the cognitive load quietly increases. The clock keeps ticking, and before you realize it, you are scrolling back through an hour-long thread trying to remember where the conversation actually began.

What you’re left with is high-quality information that feels difficult to use. The content is strong, but the volume makes it hard to know where to start, what matters most, and what should happen next.

Why this feels different than traditional collaboration

Think back to how this kind of work used to happen… A team would gather for an hour to talk through a challenge. The discussion might be messy or incomplete, but the meeting typically ended with a short list of clear actions. Those actions would get tested in the real world over the following days or week.

The next conversation built on what had been tried, what worked, and what didn’t. Progress was created in stages, with space between conversations for application and learning. Each session produced something manageable rather than exhaustive.

Now compare that rhythm to a long AI session…

Instead of a single layer of thinking, multiple layers show up at once. Strategy, execution planning, risk analysis, optimization, and reflection are all delivered in one continuous stream. The output contains insight, but it also compresses what used to be several working sessions into a single sitting. The result is mental overload disguised as productivity.

The real tension underneath the problem

AI tools are designed to be helpful, anticipatory, and expansive. When given momentum, they naturally continue building. Without intentional boundaries, that expansion keeps going until the user stops it.

The challenge is pacing. When everything is surfaced at once, prioritization becomes harder and decision-making slows down. Action is delayed because everything feels important, interconnected, and unfinished. Instead of moving forward, people stay in consumption mode.

A more effective way to use AI

AI works best when it supports the same cadence that strong teams already use.

Here are a few practical ways to apply that discipline.

• Define the purpose of the session before you begin – Decide whether this conversation is meant to produce strategic direction, a short action list, or feedback on work already in motion. When that purpose is met, end the session intentionally.
• Constrain the output to something actionable – Ask for a small, prioritized set of next steps rather than an exhaustive plan. Limiting the number of actions increases the likelihood that something actually gets done.

Create separation between thinking and doing – Apply what you have before asking the next question. Return to the tool with real-world results, observations, or constraints rather than continuing to speculate forward.

Pulling it all together

AI has enormous potential as a thinking partner, especially for leaders, marketers, and strategists who spend their days making sense of complex problems. That potential is realized most fully when the tool is used with intention and restraint. It comes from moving forward in clear, focused increments and allowing learning to shape the next conversation.

When AI is used to support that rhythm, it becomes a force multiplier. When it replaces that rhythm, it often leads to fatigue and stalled execution. The goal is to know when you have enough clarity to act… and then to act.