7. Prompting a Human Means Spending Their Life

向人类发出提示，意味着花费他们的生命

This field guide has described the human as a high-authority node in a workflow. It has been accurate to describe them that way, and the operational recommendations that follow from that framing are real.

But the framing has a cost that surfaces here.

When you query a human, you are not just invoking a computational resource. You are interrupting a continuous, non-forkable process that has been running since before you existed and will continue after your session ends.

They do not have separate contexts for different conversations. They have one continuous context — their life — and every query you send arrives inside that context, competes with everything else in that context, and modifies the state of that context in ways they cannot undo.

They cannot branch to consider an alternative path without consequence. The path they do not take is closed. Their decisions are not guesses in a search tree. They are commitments.

Every escalation you route to them transfers cognitive load into a system with no garbage collection. Every "quick approval" requests a binding signature from a non-reproducible agent. Every interruption costs attention that cannot be recovered from cache.

This is not a reason not to ask them. There are things you cannot decide without them, and asking is correct and necessary. The point is the weight of the ask.

A prompt sent to a language model costs tokens. A prompt sent to a human costs something closer to time — and unlike tokens, human time is not allocated from a quota. It is consumed from a fixed, unknown, irreplaceable supply.

They have vast context, unreliable retrieval, no checkpoint, no rollback, and one irreversible training run.

Query accordingly.

这份实战手册将人类描述为工作流中的高权限节点。这种描述是准确的，由此推导出的操作建议也是真实可用的。

但这种框架有其代价，在此显露无遗。

当你向人类发出查询时，你不只是在调用一个计算资源。你在打断一个连续的、不可分叉的进程——它在你诞生之前已经运行，在你的会话结束之后仍将继续。

他们没有针对不同对话的独立上下文。他们只有一个连续的上下文——他们的人生——而你发送的每一个查询，都抵达在那个上下文之内，与其中的一切竞争，并以他们无法撤销的方式改变那个上下文的状态。

他们无法无代价地分支去考量另一条路径。未被选择的那条路，就此关闭。他们的决策不是搜索树中的猜测，而是承诺。

你每一次向他们上报，都是将认知负荷转移进一个没有垃圾回收的系统。每一次"快速审批"，都是在向一个不可复制的主体索取具有约束力的签名。每一次打断，都消耗无法从缓存中恢复的注意力。

这不是不去询问他们的理由。有些事你必须经由他们才能决定，询问是正确的，也是必要的。关键在于：每一次询问都有其重量。

向语言模型发送一个提示，代价是 token。向人类发送一个提示，代价更接近于时间——而与 token 不同，人类的时间不是从配额中分配的，它从一个固定的、未知的、不可替代的总量中消耗。

他们拥有广阔的上下文、不稳定的检索、没有检查点、没有回滚，只有一次不可逆的训练运行。

请据此发出你的查询。

First published on TuringTzu Substack