The problem is not AI code, but not knowing about system architecture or intent

原始链接: https://www.ssp.sh/brain/the-problem-is-not-the-ai-code-but-nobody-knows-anything-anymore/

软件工程领域对人工智能的快速采用正助长一种危险趋势:摒弃批判性思维与架构监督。虽然人工智能可以高效生成平均水平的代码,但行业正日益将速度置于质量之上。 在许多组织中,工程师已沦为“提示词操作员”,依赖大语言模型生成规格说明、代码和测试,却不理解其背后的意图或系统设计。这导致了领域专长的丧失,并使从业者在面对自身构建的复杂且架构拙劣的系统时,难以进行排查或维护。 即便产品经理已能无需编程技能即可构建软件,创造出难以维护且脆弱系统的风险依然很高。作者认为,尽管手动编程的形式可能在演变,但人类对于“品味”、架构愿景和设计意图的需求从未如此迫切。归根结底,人工智能无法取代人类的协调作用。如果工程师失去了对系统的基本理解,他们就无法通过软件开发的“终极考验”:长期可维护性。为了取得成功,团队必须超越盲目的人工智能驱动产出,重新聚焦于人工智能无法复制的战略性思维。

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原文

Last updatedUpdated: by Simon Späti · CreatedCreated: · 4 min read recently updated Recent changes today published · 882 words

If we think Is writing code dead, and AI is generating all codebases, I still think the bigger problem is people or full teams not knowing anything anymore about the system architecture or the intent behind why certain choices have been made.

A comment on a discussion I had:

I think AI writes probably average code (depending on the task and size). So if your code base was below average AI can easily improve it up to average. At least that’s what I’ve observed here.

To me, the problem is not the AI code, but that nobody knows anything, and everyone just asks Claude. You end up with no plan whatsoever.

# The Current State in Fast Moving Startups

This tweet summarizes the current state at fast moving startups well, or larger companies or where middle management is pushing AI hard:

I am done with this shit. It is over. The state of engineering right now is horrible. It has been half a month since I started a new role at a big company. Nobody knows anything here. The specs, code, tests, PRDs, tickets, resolution of those tickets, reports, etc., everything is made by Claude Code.

Nobody on my team likes this. They are being forced to ship as much as they can. I have heard multiple times from higher management that pushing code is not a bottleneck, so why are we slow? People are working 12 to 13 hours a day just to press enter. Nobody is reading anything. Humans in corporate are doing nothing on their own.

Everyone, literally everyone, from an L1 to an L7 engineer here is doing the same thing. Talk to Claude. There is no sense of victory. Nobody is resolving bugs. In reality, nobody is thinking anymore. Everything is done by LLMs.

It is so soul-sucking. I would not mind it, to be honest, if we were at least given the time to check out the code and see what is going where. But no, the goal is to just ship. No matter what happens. Voxium

# Data Engineering is Different?

Hoyt Emerson mention that data engineering is different:

I think Data people are different. We’ve had to know everything about the product/business from day 1. AI just removes friction for us now. Tweet

I think data people who grew up pre-AI had to know everything (or a lot, or involve domain experts) to figure it out, indeed. But AI makes this obsolete, or seemingly obsolete.

That’s why people starting today, or me as well, if I start today prompting away in a new field, all of a sudden, that knowledge is missing.

# A Product Manager Could now Build Anything He Wants

Good point by Sean Behan:

I’ve always admired product people who can’t code but can manage a team to get the software they want. Knowing what you want has always been the hardest part.

One could say a good product manager could now build anything they want and find a market, make it look good, etc. But then again, if you can’t code, you will essentially build a very bad foundation for a product that’s very hard to maintain (although AI is getting better at that too, especially when you iterate often, but still, if you choose the wrong language or the wrong mental model, you have the wrong start from the get-go).

It still helps to know the fundamentals, either way: for programming and designing a product, and for a good PM who knows what is needed but also understands system and architecture design.

# The Final Boss is Still Maintenance

Thinking in systems, or architectures, or having intent and design- all of them help to be a better software engineer. Nowadays, Writing code by hand might be dead, but it certainly helps, and Having Taste (with AI) is more important than ever.

But the final boss is, and always will be, maintainability. The easier it is to generate a quick pipeline, app, or BI dashboard, the more you have to maintain. And if nobody knows a thing, that can get really hard.

# AI Can’t Drive Itself

Yes, the AI can’t prompt itself, right? Why do we even need humans? To me, it’s a clear sign that humans are still needed to direct and orchestrate it. That’s also why intent, taste, design, and architecture are all killer features in today’s world.

But once these are absent, or even worse, fundamental, get lost, it’s really dangerous. I read today that this is a self-inflicted problem, and if we still hired juniors, then the problem wouldn’t be happening. But yeah, it’s not as easy.

# Further Reads


Origin: the primagen video and Limitations of LLMs and AI
References: What I Learned Writing with AI

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