u/D34th4nge7

I'm currently worldbuilding for a story where humanity has been trapped in a simulation by aliens, and humans are slowly starting to emerge from said simulation, having to rebuild modern civilisation from scratch. Only a few emerge at first, and begin planning on how to proceed.

As soon as their numbers grow beyond a few dozen, they start implementing a market economy with a fairly free market. Because they can choose who to free from the simulation next, assume they have at least one competent economist among them, whose advice is generally heeded.

At the same time, the server farm where the other humans are still trapped has been abandoned long ago, and it is unclear how much longer the hardware can keep running smoothly, creating time pressure to get all of humanity out of the simulation before it starts glitching out too hard.

Now, with a government that is economically competent, would the fact that the population of this new civilisation is rapidly growing lead to inflation issues, assuming the growth can be mostly planned? If yes, could this inflation be managed without having to introduce drastic measures like price controls? And how quickly could the population grow every year while keeping inflation at a tolerable level?

The people hyping up generative AI keep emphasising that "AI can code much faster than a human". That is, strictly speaking, correct. The statement is very misleading, however, and betrays a total lack of understanding of what software development is about. As a Software Engineer, I wish to correct this misconception.

The AI bros frequently view all work as simply "a quantifiable amount of output divided by time" and focus purely on increasing that quantifiable amount. When it comes to coding, that's a horrible idea.

I've been working in software development for years, and anyone within the same career can tell you that more code does not equal better code, and that simply increasing the lines of code that a worker produces per day does not translate to better software, in fact, the opposite is the case.

The view of software development that many AI bros appear to have is that I spend all day staring at my sixteen terminal windows, furiously hacking away at the keyboard, and that my job can be done better if I can type faster. That part, genAI can actually help with. The truth is that about 95% of my work time is spent thinking. That part, genAI cannot help with.

The way this works is I get an issue assigned, often a bug in the software, or a feature request. I then read the issue, start looking at the affected code, and spend a good bit of time getting to know that code, so I understand what it does. If the code is well-documented and well-written, this helps me immensely at this point.

Frequently, I then have to spend quite some time, sometimes hours, researching how to solve the problem. I might have to dig through obscure forums trying to find the cause of this one hyper-specific bug that nobody else seems to ever have encountered.

Then, I spend more time actually changing the code and getting it to work as desired. This can easily take more hours. Possibly, there's more research to be done as I find out my original solution won't work.

At the end of all that, sometimes I am left with just a few lines of code changed. Behind these few lines, however, is tons of thinking and research. And while writing them, I have to think of the next person to look at this code. It must be easy to understand.

GenAI, however, simply parrots out good-looking code at record speeds. In some companies, coders are actually forced to use genAI as much as possible. These orders come from people who do not understand coding and think "more code, faster = better".

There's also the concept of tech debt. Tech debt is incurred when you implement a quick and easy fix that will cause more problems later. It is sometimes justified to take out tech debt, but you have to do it carefully. If you take on too much tech debt, this can make the code drastically harder to understand and maintain. GenAI, critically, produces tech debt at a hitherto unseen speed, and in a company with a culture that hypes genAI, this leads to thousands of lines of code per day, full of tech debt, being pushed to the code base.

This has already led to outages at Amazon, multiple ones, in fact. Turns out, AI code looks pretty, but it's quality is really bad. And these outages are only the beginning; tech debt accrues slowly, and you notice it most when you try to fix it. All these thousands of lines of AI code, added daily, will later have to be sifted through and fixed. Tragically, AI code is in no way written to be well-readable by humans.

In summary, yes, you can code faster with AI. But you'll fill your codebase with hard-to-read, brittle code, and your illusion that you've revolutionised coding and are getting ahead will be shattered the moment you realise the horrible state of your codebase, and the effort necessary to correct it.

So, no, long term, I'm not concerned I will be replaced by AI. On the contrary; once this bubble pops, coders who have never used genAI might be highly sought after.