为聪明人提供施展才华的工具
Give Smart People the Tools to Do Smart Things

原始链接: https://superuserdone.com/posts/2026-07-03-give-smart-people-the-tools/

当前的 AI 营销叙事——即 AI 即将取代人类专家——是一种在投资者要求实现实际盈利之前,为了最大化投资和依赖度而采取的愤世嫉俗的策略。通过将复杂的专业工作简化为单纯的“产物”(可见的输出),AI 公司忽视了人类专家所提供的关键性、非确定性推理、架构判断力以及商业洞察力。 历史先例表明,电子表格和 CAD 系统等强大的工具并不会取代专业人士,而是增强了他们的产出,使他们能够处理更复杂的任务。AI 本应遵循这一路径。然而,目前各公司优先考虑的是耸人听闻的“网络武器”言论和消费者未来主义,而非实际效用。这种营销贬低了专家们一丝不苟的工作,掩盖了一个事实:真正的价值在于过程,而不仅仅是产出。 作者认为,AI 高管们应该摒弃那种威胁性的“取代”叙事。相反,他们应专注于开发能够赋能专家、使其工作更高效的专业化工具。正如游戏引擎让小团队能够构建宏大的项目一样,AI 应被定位为人类专业能力的倍增器,而不是取代专业工作价值核心的智慧的替代品。

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原文

Have you opened X or a tech news site lately? Then you are probably familiar, even exhausted by, posts like these:

Do you want to hear a secret?

This is marketing.

The message is simple:

AI will beat the smelly humans. It is faster, cheaper, tireless, and anyone who doubts this (usually the experts in a field) is a dumb luddite who failed to adapt (and will end up in the permanent underclass).

Conveniently, adaptation means buying the $200/mo subscription and convincing your boss to spend $4000/mo on tokens so you can work faster/better/harder.

Artifacts are not Work

Compilers did not replace programmers. Spreadsheets did not replace accountants. CAD systems did not replace engineers. These tools changed what competent people, the experts, could do, how fast they could do it, and how much complexity they could manage.

A compiler can translate code, but does not understand software. A programmer does. A spreadsheet can calculate, but does not know what calculations are important for the next quarter. An accountant does. CAD can model a bridge, but it cannot decide whether to simply upgrade the one 200 meters downstream. An engineer can.

Visible output is just a small part of the actual job done. AI companies reduce work to the visible output, the artifact, completely ignoring the value in understanding that comes from the process of producing that artifact.

In programming, the bottleneck is understanding the business problem, designing the system architecture, and maintaining the codebase. Sure, you can write the perfect prompt to encapsulate your entire business problem. Ask any business that tried outsourcing in the last 30 years, they might have some tips if you want to go down that path… The hard thing is knowing if something is good, what tradeoffs it makes, and the consequences of a particular implementation or choice.

Code is designed to be deterministic. The idea that a probabilistic system will replace compilers is fundamentally silly.

The same thing is starting to happen with cybersecurity. Take the Mythos/Fable release from Anthropic. Among the serious security people I know, the reaction to Mythos was not awe. It was frustration: Anthropic took a genuinely interesting capability and wrapped it in reckless “cyberweapon” marketing. Also, no it did not hack the NSA. The damaging claims around AI “cyberweapons” devalues the meticulous work of actual security researchers and pentesters, and overshadows the actual capability of a model like this.

Here’s the thing

All of these AI companies are facing a massive problem. Currently, there is a huge amount of investor appetite for AI. The AI companies know it won’t last.

Selling “the future” for investment will soon give way to investors demanding something in “the present”. At some point numbers start mattering. Quarterly revenue, customer retention and margins. Customers asking: “did this really save us money?”

They are capitalising on the hype while it lasts, and convert hype into capital, customers and dependency before investors start caring more about margins than mythology.

Assist the work, not just the artifact

I have a dream about the future of AI. A dream where AI complements human experts, rather than threatening to replace them.

Back when tools like Unity and Unreal were released, they drastically lowered the barrier of entry and more low-quality asset-flip games were made. They did however allow smaller teams of people and solo developers who genuinely had the skills to make games, to build their dream project without sacrificing on technical scope due to not having the resources to develop their own game engines from scratch.

This is an example of tools empowering creation and innovation, and yes there is a cost to it too (asset-flips).

Midjourney Medical is interesting because the underlying idea points in the right direction: better tools for people with expertise. A tool like this could give doctors and researchers better, less invasive insight into the human body. That does not “cure cancer” by itself, but it could make experts dramatically more effective at diagnosis, research, and treatment. But the bougie spa/wellness framing also shows how quickly even useful technical ideas get wrapped in consumer futurism.

With all that in mind.

Hark my request AI executives

Give smart people the tools to do smart things instead of threatening that you will replace them with a clanker.

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