I'm not convinced the bad market is due to AI at all. That's just a convenient excuse to do layoffs without the bad PR normally involved in admitting you need to do layoffs.
Also, the Open to Work banner has the stink of desperation. Highly recommend disabling it. It's like dating. Act casual.
I think it is both a partial contributor but also overstated for the reason you mentioned. The main culprits IMO are over hiring during the zero interest rate period as well as the never ending increases in the supply of CS graduates.
I believe it's not only the supply of CS graduates, it's their training as well. CS education seems to have changed little over the past 50 years. While the skills needed today are drastically different than those needed 10 years ago.
I have little doubt that if I had an opportunity to use Claude to do my CS homework, I would have used it. It seems that the curriculum should assume that college kids are going to use the latest agents and dramatically increase how hard the homework is.
I think the point is that the banner is more likely to extend your search by sending a negative signal than it is to speed up your search. Fair or not, potential employers often have a negative bias toward people who are unemployed, so indicating that you’re likely unemployed is unhelpful.
No real idea why this bubbled to the front page, as it’s just another milquetoast subjective take from a single point of view recapping the same events from their context. Nothing added, no food for thought, just the same old, same old.
We need less folks ringing alarm bells without guidance and more folks offering help in troubling times. This, is not helpful.
> He has a huge influence on the developer community, and he is deceiving his viewers about what is going on.
The sub bubbles of development are so crazy to hear about. Idk if I ever interact with anyone that gets their development world view from people on YouTube.
Idle thought. Not an economist.
What if the current tech scene is like how the u.s. capitalist class took power away from blue color workers in the 80s, 90s by leveraging cheaper labor in foreign countries? Now, programmers, sysadmins, system engineers no longer have leverage (real or imagined) because the owners just point to AI.
If they could do it, they would. White collar workers don't have any special status that protects them from getting the same treatment the blue collar workforce got. That said, I think it'll play out differently this time.Offshoring blue collar jobs eventually hurt the capitalist class; they lost whole industries to China. Offshoring white collar jobs is a different kind of risk: you end up with IOUs to countries that might not stay favorably disposed toward you when the power dynamics shift.
I have to wonder how GenAI would have fared if these LLMs had become available anytime before 2020, during the “normal” tech bubble. It feels like the faith in it is as much to slash costs while appearing to be cutting-edge (and thus, worthy of what little investment is still available), as it is because of its capabilities. Where would we be if the tech industry wasn’t in such a dire state due to the end of ZIRP?
What happens to a society where one class extracts payment from another class but the payment only flows in one direction and eventually the latter class doesn't have it, and outnumbers the former class?
What happens when a creative writer pens an influential treatise on economic and politics, but it turns out he was completely wrong on many key empirical aspects of human behaviour, leading to tens of millions of deaths, yet his followers will not see his failure and keep trying to turn over society to produce his false utopia?
Personally, I believe that the supposed productivity gains of LLMs will turn out to be much like outsourcing to India around the turn of the century: managers think it's a great idea to cut costs, but it will also make quality plummet, and there will be a correction back towards sanity. That doesn't mean that everything is all roses - even if the market will get over the AI insanity someday, that's cold comfort if you're out of a job right now. But I do think that it's not going to be "if you aren't on board, then gg" in the long run.
I have already seen multiple CLs from people who are both senior and junior where I know they did not look at the code. I thought, at first, they worked and upon review it looked good but when I synced these changes I found either big bugs that a human would never make or a test would never catch or lots of code repetition.
One example was an engineer who was refactoring some code that ended up doing this:
def execute(jobs):
for job in jobs:
asyncio.create_task(compute(job))
yield await compute(job)
This is very simplified, it as actually broken up into two separate loops and hidden behind multiple nested calls but at some point there literally was a `asyncio.create_task` where the result was not being used.
I looked at this code because we were hitting some quota limits very early for some reason and it turned out we ran 2x the reads we needed to. I refactored this code, 1/2ed the execution time, fixed the quota issues, and took it from ~300 lines to 80 lines.
This was code from a *senior software engineer* with 15 years in the industry. What is very interesting is I see similar bugs from juniors who do or don't use AI.
I am not saying AI can't be useful. On weeks I have had clear tasks set out, while the rest of my team was OOO, I tackled probably 5x the work our team normally accomplishes (this was after all the work was identified, just working). My skip actually said "Wow, we had a very productive week!" so multiple layers noticed the productivity. I think what made this possible was:
1. I fully understood the **entire** task and the end-user needs.
2. The code base was structured "fine" with enough decoupling between components that I wasn't hitting merge conflicts with myself.
3. I self-reviewed all the work before sending anything to other people (opened all the changes in my IDE, read all the tests).
4. If something seemed too complicated I refactored it manually.
5. I left the AI chugging for long periods of time on objectively measurable tasks.
I don't think the practice of engineering software is dead. The architecture of your software now has measurable impact on productivity. I don't think thinking about performance is outdated. If you're running code no one has reviewed but is functional you wasting cycles / money. Having domain knowledge still improves your velocity.
Because of these reasons I think there is still marginal value to programmers. Companies which maintain internal talent pools and build tooling to scale the impact of people will probably beat out smaller companies that just vibe code.
Also, the Open to Work banner has the stink of desperation. Highly recommend disabling it. It's like dating. Act casual.
I have little doubt that if I had an opportunity to use Claude to do my CS homework, I would have used it. It seems that the curriculum should assume that college kids are going to use the latest agents and dramatically increase how hard the homework is.
We need less folks ringing alarm bells without guidance and more folks offering help in troubling times. This, is not helpful.
> He has a huge influence on the developer community, and he is deceiving his viewers about what is going on.
The sub bubbles of development are so crazy to hear about. Idk if I ever interact with anyone that gets their development world view from people on YouTube.
You’re pretty much spot on.
One example was an engineer who was refactoring some code that ended up doing this:
This is very simplified, it as actually broken up into two separate loops and hidden behind multiple nested calls but at some point there literally was a `asyncio.create_task` where the result was not being used.I looked at this code because we were hitting some quota limits very early for some reason and it turned out we ran 2x the reads we needed to. I refactored this code, 1/2ed the execution time, fixed the quota issues, and took it from ~300 lines to 80 lines.
This was code from a *senior software engineer* with 15 years in the industry. What is very interesting is I see similar bugs from juniors who do or don't use AI.
I am not saying AI can't be useful. On weeks I have had clear tasks set out, while the rest of my team was OOO, I tackled probably 5x the work our team normally accomplishes (this was after all the work was identified, just working). My skip actually said "Wow, we had a very productive week!" so multiple layers noticed the productivity. I think what made this possible was:
I don't think the practice of engineering software is dead. The architecture of your software now has measurable impact on productivity. I don't think thinking about performance is outdated. If you're running code no one has reviewed but is functional you wasting cycles / money. Having domain knowledge still improves your velocity.Because of these reasons I think there is still marginal value to programmers. Companies which maintain internal talent pools and build tooling to scale the impact of people will probably beat out smaller companies that just vibe code.