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Comment by walrus01 | Hacker News Reader

LLMs reward architecture knowledge of how to structure things and how to not just say "Claude, make me Microsoft Flight Simulator, make no mistakes".

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Many, including myself, report having a lot of success with braindumping and not structuring anything. Just talking into speech recognition for 2-10 minutes as a stream of consciousness about what my context is, what I want, what I know already, what I have a vague hunch about, how it fits into a bigger picture, what aspects are most important to me, any footguns I already know about, really like having a chat with a person on the phone, with someone you have to guide remotely because they have to implement the thing right now but you have to be out of office and so your only interface is speech. Except you can be more structureless because the AI won't be offended. Just keep on rambling, and press enter, don't even correct mistranscriptions. It will understand it anyway.

Now, the key is, that while rambling without structure, you do have to drop the key facts into your speech, and you have to know what you're talking about in at least a good portion of it.

I think people are afraid of doing it, because it seems "not the right way" or "not scientific" or whatnot. They want to believe there is some magic to writing the right prompt. So let me tell you, it works.

I don't completely disagree with the concept of giving a free association thought process ramble into context. But I also bet that when you start getting it to actually generate code and link modules of things together, subroutines, functions, code structure and filenames, you still pay attention to what it does and you guide it into the architecture that makes logical sense to you.

For real work yes. For personal projects, less and less since Fable came out (probably the same if true of the other frontier models). You can get a lot done if it's just some one off, or a personal tool, even without looking at the code, just trying the application. Frontier models now automatically test it before handing the thing to you, they take screenshots, they fix the superficial issues themselves. To get something up and running, it's enough to send chat messages.

Unfortunately the software industry is saying things like "don't look at the code", "LLMs have made developers 10-100x faster", etc. The only way they can make such claims is by saying what you said above: "Claude, make me Microsoft Flight Simulator, make no mistakes". Additionally engineers are facing pressures via deadlines to work in the paradigm of "Claude, make me Microsoft Flight Simulator, make no mistakes"...

The question i wonder about is, when will an event come along that persuades everyone that human understanding is still required? Or will it never come?

Such an event would have to be pretty catastrophic at this point to slow down the inertia. Perhaps the tech debt will just pile up until someone's product implodes, or there's a massive safety issue that causes loss of life, or some big hedge fund goes bust.

I wonder the same thing. I think we've already seen some of this happening, however the consequences haven't been large enough to the organization, for example:

- https://www.theguardian.com/technology/2026/mar/20/meta-ai-a...

- https://tech.yahoo.com/articles/ai-code-wreaked-havoc-amazon...

- https://alexeyondata.substack.com/p/how-i-dropped-our-produc...

We can only hope that engineers working in safety critical systems haven't fallen to these working conditions.

As long as people keep gaslighting by sayting those events are just "skill issues," I doubt there will sadly be a catalyst.

Yeah, this will never happen until governments step in and cause these companies real pain. I mean just look at Crowdstrike. They caused billions and billions in economic damage due to their incompetence, and nothing happened. In fact, their stock is close to an all time high.

That question makes me think about Boeing. Or NASA. Or Enron. Reality always wins, no matter what management and Investor Relations says.

It makes me think about The Terminator.

The event could be when fair pricing comes from the model providers. We're still at the cash burning stage. When the economy crashes a little and departments start monitoring their spending, and the prices for inference are 10x what they are, there will be less tolerance for employees to substitute constant AI usage for understanding.

You're assuming that LLMs entered a world of people who understood how the systems they're inside of work, why they're setup that way, and that LLMs are displacing them. I sadly don't think that's the case in... well... a lot of the cases.

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