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> out of all the fascinating and awful things to care about with the advent of ai people pick co2 emissions? really? like really?

Yes. Because climate change is real. If you don't believe that then let your LLM of choice explain it to you.


> till the poor colleague ran out of arguments

I hope your colleague was agreeing to partake in this experiment. Not even to mention management.


Buy high, sell low. Excellent result when you follow the masses, especially when being a little late.


Where was I giving that advice? Gold and silver mining stocks are extremely low compared to the price of gold and silver buying mining socks right now is buying low.


AUAU ETF crashed 11% today... Ask me how I know that :(

Skill. Knowledge. At your age, your biggest assert is your future earnings potential. The more employable you are, the better you will make iduring and after a downturn. In fact, the highest skill folks tend to even profit from hiccups in the economy.


Are the ones newer to the workforce just screwed or is there a way out? Kinda sucks that all this went down around 6-7 years into my tenure and it's just been a few years of scraping together freelance + portfolio projects to try and climb out of tbis rut.

(This might sadly be rhetorical given what I hear of '08, but perhaps there are new channels open to take advantage of. Or at least old channels to raise awareness of).


Newer ones are definitely screwed.

6-7 years of experience make you prime material for employment in the sw industry. Experience but not too expensive/entitled yet.

Have you considered applying?


Yes. And here I am nearly 3 yesrs post last full time, 9 years of exexperience, and still looking (feel free to read my struggles in detail below).

What do you recommend applying to? I work in games so I guess I'm playing on hard mode (especially in these times), but the common wisdom of "normal software jobs love taking game programners in" hasn't rung true this time around.

----

Life story: Laid off mid 2023. I took a few months off when I got laid off, but the last quarter of 2023 wasn't kind to me.

2024 got me some freelance work, so I wasn't out on the streets, but it was a complete circus of an interview racket. Honestly worse than my first job hunt out of college. Its bad when you feel deep down there was someone better than you, but when you go 5 rounds in with good vibes to hear... Nothing back? That's truly disrespectful. And it sadly wasn't a one off.

Then in 2025 I hit some medical emergencies so I needed to urgently find anything. So I found part time work outside of tech and made due with that as I paid down those debts. That totaled up to a part time freelance gig, a part time job, and a few (failed) attempts at some hustles over 2025 only to end up making maybe a third of what I made back in 2022.

Now it's 2026 and I'll try again next month. My freelance work covers any gaps I would have had, I have a website almost ready with some personal projects to point to, and I'm overall more adjusted to the realities of this current market and will approach accordingly. I'm optimistic, but I know we're still in the thick of the weeds here. So I'll take any leads I can get.


None of that is true. Not one word of this applies anymore. Being highly skilled means you're highly paid, which puts you first in line for cuts. Talent doesn't get you hired, networks do. "Future earning potential" is just nonsense words, you can't eat "future earning potential".

This advice is from half a century ago. The times have moved on.


What's your advice then, if it's not investing in your hireability?

> We'd rather lose the source code than the knowledge of our workers, so to speak.

Isn't large amounts of required institutional knowledge typically a problem?


It was a "high tech domain", so institutional knowledge was required, problem or not.

We had domain specialists with decades of experience and knowledge, and we looked at our developers as the "glue" between domain knowledge and computation (modelling, planning and optimization software).

You can try to make this glue have little knowledge, or lots of knowledge. We chose the latter and it worked well for us.

But I was only in that one company, so I can't really tell.


> I automate nearly all my tests with AI

How exactly? Do you tell the agent "please write a test for this" or do you also feed it some form of spec to describe what the tested thing is expected to do? And do these tests ever fail?

Asking because the first option essentially just sets the bugs in stone.

Wouldn't it make sense to do it the other way around? You write the test, let the AI generate the code? The test essentially represents the spec and if the AI produces sth which passes all your tests but is still not what you want, then you have a test hole.


I'm not saying my approach is correct, keep that in mind.

I care more about the code than the tests. Tests are verification of my work. And yes, there is a risk of AI "navigating around" bugs, but I found that a lot of the time AI will actually spot a bug and suggest a fix. I also review each line to look for improvements.

Edit: to answer your question, I will typically ask it to test a specific test case or few test cases. Very rarely will I ask it to "add tests everywhere". Yes, these tests frequently fail and the agent will fix on 2nd+ iteration after it runs the tests.

One more thing to add is that a lot of the time agent will add a "dummy" test. I don't really accept those for coverage's sake.


Thanks for your responses!

A follow-up:

> I care more about the code than the tests.

Why is that? Your (product) code has tests. Your test (code) doesn't. So I often find that I need to pay at least as much attention to my tests to ensure quality.


I think you are correct in your assessment. Both are important. If you're gonna have garbage code tests, you're gonna have garbage quality.

I find tests easier to write. Your function(s) may be hundred lines long, but the test is usually setup, run, assert.

I don't have much experience beyond writing unit/integration tests, but individual test cases seem to be simpler than the code they test (linear, no branches).


> Hopefully they're able to track down who did this.

Why? Was anybody harmed?

Hopefully they don't find out who did this. There was never any danger, and without this kind of joke, the world would be less fun.

(Obviously it should be harder to fool critical systems, so this served also as a warning, but if you want to attack such a system, a real bad guy would do this in more subtle ways.)


In your mind, what is the difference between a mathematical abstraction and a natural construct?

Asking because to me, any mathematical abstraction is a natural construct. Math isn't invented, it's discovered.


Look around you. Our industry has cultivated that this kind of software is everywhere.


It's... really just not, though


There are isolated islands of reliable, high quality, low bug, well maintained software. The rest is crap.


> the problem is two fold

No, the biggest problem at the root of all this is complexity. OpenSSL is a garbled mess. No matter AI or not, such software should not be the security backbone of the internet.

People writing and maintaining software need to optimize for simplicity, readibility, maintainability. Whether they use an LLM to achieve that is seconday. The humans in the loop must understand what's going on.


> People writing and maintaining software need to optimize for simplicity, readibility, maintainability. Whether they use an LLM to achieve that is seconday. The humans in the loop must understand what's going on.

In a perfect world that is.


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