Stop Telling Me to Ask an LLM

别再让我去问大模型了

I’m a million times more likely to send an email or a text than to pick up the phone. But I had a question I thought was worth an actual call, so I scheduled one with someone senior enough to have real scar tissue, the kind you only get from watching a decision go sideways in a boardroom. I asked him where he’d look, personally, for the answer to a hard question I was chasing, one without industry consensus. Not what the textbook says. If five studies conflicted, which would he trust? I wanted the thing 30 years had taught him that a search engine couldn’t.

比起打电话，我更倾向于发邮件或短信，概率高出一百万倍。但当时我有一个问题，觉得值得打个电话沟通，于是我约了一位资深人士，他有着丰富的实战经验——那种只有在董事会决策失误时才能磨练出来的“伤疤”。我问他，如果换作是他，会去哪里寻找我正在追寻的那个难题的答案，毕竟这个问题在业内还没有共识。我问的不是教科书怎么说，而是如果五项研究结论冲突，他会信任哪一个？我想要的是他三十年经验积累下的智慧，那是搜索引擎无法提供的。

“Honestly? Ask Claude.”

“说实话？去问 Claude 吧。”

That stung a little, but it wasn’t the first time I’d heard it. Once it was a data problem I’d been stuck on. I’d approached it a half dozen different ways and could explain in some detail why none of them had worked. I reached out to a few people who do this kind of thing for a living, people I text with regularly, trading questions and working through whatever we’re stuck on. All but one gave me the same redirect.

这话听着有点刺耳，但这已经不是我第一次听到了。有一次，我被一个数据问题难住了。我尝试了六种不同的方法，并且能详细解释为什么它们都行不通。我联系了几位以此为生的人，他们是我经常发短信交流、互通有无、共同解决难题的朋友。除了一个人之外，其他人都给了我同样的回复，把我推向了 AI。

Each time this happened, I had already asked Claude. That wasn’t the step I’d skipped. Before I ever reached out to a person, I’d spent a couple of hours (and sometimes way too many tokens) going back and forth with a large language model, and I still had a question that had survived all of that.

每次发生这种情况时，其实我都已经问过 Claude 了。那并不是我跳过的步骤。在联系任何人之前，我已经花了好几个小时（有时甚至消耗了过多的 Token）与大语言模型反复沟通，而我剩下的那个问题，是连模型都没能解决的。

I’m old enough to remember people sending LMGTFY links to folks who didn’t seem to know how to use a search engine and expected strangers to do unpaid research for them. But this isn’t that. It’s closer to what happens when I ask a friend for a food recommendation and get a top-10 list back. I’m not asking what Eater thinks is the best kind-of-quiet spot for late-night drinks, or for a great coffee shop in the city where they used to live. I’m asking what they think, because we have similar taste and a shared history, and because I know they have opinions about where the lists go wrong. I trust their experience over the expert consensus.

我年纪够大，还记得当年人们会给那些不会用搜索引擎、指望陌生人免费帮他们做调研的人发送“LMGTFY”（Let Me Google That For You，让我帮你搜一下）链接。但现在的情况并非如此。这更像是当我向朋友寻求美食推荐时，却收到了一份“前十名榜单”。我不是在问美食网站 Eater 认为哪家店适合深夜小酌，也不是在问他们曾经住过的城市里哪家咖啡馆好喝。我问的是他们的个人看法，因为我们品味相似、经历相通，而且我知道他们对这些榜单的局限性有自己的见解。比起专家共识，我更信任他们的经验。

It’s possible “ask the model” has become the polite version of “I don’t know,” or “I don’t have time for this right now,” or “I’d have to think about it.” Maybe it’s an easy way to decline giving an answer. But I’d take almost anything over the redirect. “I’m busy” is a real answer. “I can’t think of anything you haven’t already tried” is an answer too. What “ask Claude” doesn’t give me is the person’s specific, lived experience. That’s the thing that’s hard to write down and even harder to search for.

或许“去问模型”已经成了“我不知道”、“我现在没时间”或者“我得再想想”的委婉说法。也许这只是一种拒绝回答的简单方式。但我宁愿听到任何其他回答，也不愿被推给 AI。“我很忙”是一个真实的回答，“我想不出你还没试过的方法”也是一个回答。而“去问 Claude”无法提供的是那个人的具体生活经验。那才是最难被记录下来，也最难被搜索到的东西。

There’s a real cost to being the person other people call, and it’s not fair to expect everyone to bear it. It takes close attention and actual thought, and not everyone has that to spare on a day full of deadlines and fires to put out. Plenty of questions really can be answered by an LLM or a search engine. But when the question is one that already survived the model, “ask Claude” doesn’t save anyone a step. It just withholds the thoughtful answer decades of experience could have given.

成为那个被他人求助的对象确实需要付出代价，要求每个人都承担这种责任是不公平的。这需要全神贯注和深度思考，并不是每个人在忙于应对截止日期和处理突发状况的一天里都有余力去做这些。很多问题确实可以通过大模型或搜索引擎解决。但当问题已经经过了模型的筛选依然存在时，“去问 Claude”并不能节省任何步骤。它只是掩盖了那些几十年经验本可以提供的、深思熟虑的答案。