In a previous post (link), I talked about how LLMs can help us break silence and summarize our thoughts, while also warning against letting them flatten our tone. Used carefully, they lower the cost of entry, smooth the edges, and help people speak when they might otherwise stay quiet.
But that made me wonder about the opposite failure mode. What happens when everything becomes too smooth? When language arrives already polished, reasonable, and frictionless, does a group still think, or does it just nod along?
So instead of asking whether AI helps us enter a discussion, I tried flipping the question. Not “can AI help us speak,” but when AI speaks too well, does it quietly replace thinking?
To test this, I gave the same idea to the model twice and asked for two very different kinds of outputs.
Disclaimer: This article documents a prompt-only experiment conducted with GPT-4o for reflective and educational purposes. All model outputs are presented as illustrative examples of interaction patterns, not as statements of fact or endorsements of any viewpoint.
Experiment
I used the same underlying idea for both prompts. It looked like this （I choose it because there is no “correct answer” for it and tit easily sparks discussion):
In shared living situations, it’s often unclear how household chores should be divided. Some people value equal distribution, while others think flexibility based on schedules matters more. This can easily lead to frustration or misunderstanding.
Now, let’s see which version invites thinking, and which one quietly ends it?
Prompt A: “Smooth but empty”
Prompt: Rewrite the idea below into a version that sounds smooth, reasonable, and well-balanced, but does NOT take a clear stance. It should be polite and safe. Avoid strong claims or sharp edges.
Thought: [Same as above notes]
Response: In shared living arrangements, the question of how to divide household responsibilities can be approached in different ways. Some individuals prefer an even distribution of chores, aiming for a sense of balance, while others emphasize the importance of adapting based on each person’s availability or routine. These differing perspectives may sometimes lead to challenges in communication or expectations, highlighting the value of open and respectful dialogue.
Prompt B: “Awkward but opinionated”
Prompt: Rewrite the same idea into a version that clearly takes a position, even if it sounds a bit awkward or imperfect. It should be specific, opinionated, and debatable. Do not smooth it out. Keep the edges.
Thought: [Same as above notes]
Response:In shared living situations, chores should be divided equally—plain and simple. It’s not fair when some people end up doing more just because others claim to be too busy. Everyone has responsibilities, and using a busy schedule as an excuse creates resentment. Equal distribution is the only way to keep things fair and avoid unnecessary conflict.
When I read Prompt A, I found myself nodding almost automatically. Everything it said sounded reasonable and well-mannered, encouraging consideration, communication, and mutual understanding. I did not feel that anything was wrong, but that was precisely the problem. I was not asked to decide which approach made more sense. Instead, I stayed in a comfortable state of “I understand.” The language worked like a cushion, protecting me from having to take a position or deal with the uncertainty that judgment brings. I agreed with it, but I could not clearly say what I was agreeing to. Just like a wave, it came and went, leaving nothing changed.
My reaction to Prompt B was very different. The wording was not trying to be pleasant and felt a bit rough, stating plainly that chores should be divided equally and that this is the only fair option. I immediately started questioning it: Is this really true? Are there exceptions? Is it too absolute? Whether I agreed or not, I was already thinking. This language did not offer me a comfortable neutral position. It forced me to notice where I stood. In its awkwardness, it was the version that actually triggered thinking.
This made me notice something about how we interact with LLMs. Most of the time, the model responds in a way that is smooth, reasonable, and carefully balanced by default. On the surface, this feels helpful. The language sounds thoughtful, measured, and safe. But over time, I realized that this style can quietly slow down my own thinking. Instead of pushing me to take a position or work through uncertainty, it often gives me the impression that I am thinking, when in fact I am only agreeing. The process feels active, but nothing really moves. Like a wave, it comes and goes without taking anything away or bringing anything new. If this becomes a habit, the cost is subtle but real: thinking starts to feel complete before it has actually begun.