Cost is a big factor, but so are modern building codes. Some classic architectural features are outright illegal to build in 2026. Others might be allowed, but there's almost no one left who knows how to do it (e.g. plaster walls or ceilings).
Robots are not going to bring any of this back because robots will just create a new set of optimizations and constraints needed to make robotic construction cheaper and easier. If modern cars (which are the result of similar optimization) are anything to go by, this will result in output that's easy to build but hard to maintain or modify - so largely a continuation of existing trends.
Take a look at "3d printed" houses for an imperfect example of this kind of optimization for automation in action. Better robotics will bring about a more balanced version of this trade-off (walls will probably be possible to modify, unlike 3d printed ones) but the incentives remain the same.
Edit:
Trivial example: One of the easiest way to autonomously insulate a house will probably be with spray foam insulation - you can get a robot arm to hold the sprayer and move it in a specific, continuous motion pretty readily even today. But spray foam insulation is hard to modify after the fact. Removing it is time-intensive compared to removing insulation "batting" and applying it again requires specialized tools, PPE, and perhaps licensing.
But in chemical science you would not "understand" everything. You cook with ingredients where you don't fully understand then.
There are always limits.
Engineering human types are often guilty of saying something is low cost but then not doing it themselves. Great, "understand everything".
Trust us trust. You trust an entity. What the author is describing is a new kind of transaction. It's not that AI causes people to lie suddenly (although if you trusted the wrong people this might happen to you, but YOU were wrong then) but now you have a lot of work being done more at the edge of uncertainty and recommendations. Ideas are not ideas anymore, they are working implementations.
So instead of submitting discussions or requests for features, you literally submit implemented features because the cost is lower. This is good. You just have to realize that you are starting the discussion with a working implementation. If you continually try to act like this is not the case, without someone literally lying to you about it, this is more about just accepting a now workflow.
The real annoying thing it seems is mostly that openai is presumably doing this for internal reasons and this marginally increases the cost to users with no real gain.
It would be one thing to gain from it but removing prestige wins from customers AND reducing compute support just feels like being ultra mean if you zoom out.
If this was racing to cure cancer ahead of researchers we wouldn't be writing about this on HN.
Depends on your usage. A rubber duck won't upheave the entire history of written human knowledge to reach for your answer. It doesn't have inherent bias, and its purpose could also be handled by a wall, or the air infront of you if you can stretch your mind a little. What I'm going for here is that as you said, its just a hack to make your brain look for answers in a more efficient manner, by clearly underlining your thought process out loud, tricking yourself into conversation mode, yada yada. Its still you doing all the work, you're just being smarter about it.
A LLM is more akin to a senior pair programmer. It may seem like a rubber duck on the surface, in the sense that you're having a conversation, but the senior programmer may come up with ideas you wouldn't think of. They may have more innate experience in the domain which might pull you away to very different implementations from what you had in mind initially. This is all good, but a common pitfall with LLMs is that they're much more conformative than a senior engineer, much faster, much more responsive. This is where it gets dangerous: they don't tell you you're wrong 80% of the time, like a rubebr duck. They also have innate experience of a domain, like a senior engineer. The result is that your brain never gets a 'hang' signal, and it doesn't feel the need to reevaluate.
I don't know, it seems more like every question goes to a contract agency, where a random programmer answers it. Generally they are very good at bringing up relevant things you've never heard of, but depending on who gets assigned to that answer, the implementation might be copy-pastable into production, or it might be a questionable hack, or it might be workable but clearly not the right approach if you're looking for those things. The agency must work by the hour, though, because if you challenge the assertions of the previous guy, the next guy will obsequiously say that you are, of course, quite right and possibly insightful and spit out a new solution more along the lines of the new guidance.
Just that an actual rubber duck doesn’t do anything. You solve the problem you have by talking, and in doing so, thinking, to come up with a solution, an idea, or gain better understanding.
After that you either implement something yourself or have learned something.
With an LLM you offload all of that, the only thing you still do is tell it what the problem is. The agentic duck does the rest and you look at the output.
Even if you have to argue, you argue without having gone through the steps to gain anything yourself.
Markets solve this by pricing risk. Ideally you would have some kind of notion of selling insurance internally and track things. But ultimately existential risk is hard to negotiate from the inside. And companies are supposed to go bust or succeed. They are not really the same as a population trying to survive forever. At least that is one take.
I have many projects going, many tmux sessions, but I also found I don't resonate with the post either. Yes, there are times I use AI and it doesn't go anywhere and wasn't necessary but I don't think I can always know that ahead of time. The point is the overall pattern and the actual of useful work.
I am much more able to use fragmented bits of time now. Whereas before if I had 20 minutes here and there I would not be able to even read code or notes in order to get context enough to make a change let alone do real work.
I suspect personality matters. Often in discussions with AI or anyone I tend to take opiate position and constantly challenge and dig in. I don't go with the flow. With people this can be problematic. With AI it merely takes more time but probably a avoids some pitfalls.
They are comparing "same buildings" with AI but I would imagine they are not controlling cost.
Imagine gargoyles and metal dragons on drainpipes and all the ornamentation now and how much that would cost.
People prefer ancient dry stone walls over fences but they cost orders of magnitude differently.
I wonder if with robots and what not if we will see a resurgence in detail and ornamentation and other kinds of expensive but nice constructions.
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