Comment by littlecranky67
4 days ago
The thing is the have been told to use the tokens wisely, but no limit is communicated. Still everybody is hesitant. To be fair, the company runs claude on AWS bedrock for data privacy requirements at a different pricelevel. But I guess that is the drawback for german job-security: each and all of them know they basically can't get laid off.
I also attribute a lot of it to be just plain outright denial. I have a feeling a lot of people don't WANT to understand that their coding skills they acquired over years have dropped a lot in worth. It is the "as long as I don't step on a scale, I can't be overweight" kind of denial. You are afraid to see what is behind the curtain, so you simply don't do it.
> But I guess that is the drawback for german job-security: each and all of them know they basically can't get laid off.
Help me understand what exactly is the drawback you’re mentioning. In your previous comment you were suggesting these people spend their own personal money and personal time on projects to benefit their work time. They (quite reasonably, it seems from the limited context) decided that no, they won’t dedicate life and resources from outside work to more work. Fortunately, it seems they have some job security (German, but probably some from the EU as well) which allows them to make whatever choice they believe is healthier to them, without fearing repercussions. What’s the drawback?
The obvious drawback is that according to his description, they aren't getting much done and neither are they producing quality work.
This would check out with the fact that there aren't many software products or platforms made in Germany, compared to say the US or China.
This raises questions about how sustainable this situation is and if it might further increase the gap in income of software engineers in the US compared to Germany.
Even the best benefits do arguably not make up for receiving $2500 net at the end of the month compared to $8k in the US.
And I get what you are saying about work life balance and so on, but if one cannot even be bothered to try a $20 AI subscription at home, there must be about zero passion for the craft.
> The obvious drawback is that according to his description, they aren't getting much done and neither are they producing quality work.
That’s not what the description says. Not being a rockstar does not mean being incompetent. They claimed (and let’s not forget this is one person’s account) the devwork of those people could be replaced with AI. Even assuming that is true, that does not mean their current work is bad or that they can’t improve, or that they don’t have other valuable skills.
The drawback you’re listing there, in addition to being dubious, seems to be exclusively for the owners of the company. What about the workers?
> This would check out with the fact that there aren't many software products or platforms made in Germany, compared to say the US or China.
Good. I don’t think the software products coming from the US and the culture of exploiting people for profit are a net positive for humanity. I’d rather not have those companies, so a system which prevents that from happening is working as it should.
> Even the best benefits do arguably not make up for receiving $2500 net at the end of the month compared to $8k in the US.
Happiness reports disagree.
https://en.wikipedia.org/wiki/World_Happiness_Report
You don‘t need to earn a lot of money when your basic needs are met. Like not worrying that a sudden illness will bankrupt you.
> And I get what you are saying about work life balance and so on, but if one cannot even be bothered to try a $20 AI subscription at home, there must be about zero passion for the craft.
Why must that be the way? Perhaps they instead believe they can and should improve in other ways, including understanding that you can’t learn without doing, and delegating your tasks to LLMs prevents you from doing so. Seems very strange to claim that the programmer who does not use AI is the one lacking passion for the craft.
4 replies →
No you misunderstood my comment. I suggested they spent their private money - 20€ a month for the lowest Max flatrate tier - because to me it is obvious that you absolutely need to develop the skill to work with AI. They only have the "pay-per-token" model on their work accounts and laptops, because that is what large corporations get - no flatrate. That leads them to not work with AI. Most of them just refuse to get that 20€/month subscription to experiment with it on their private laptops. I didn't say private time - company policy is no US cloud services for work related topics so they would have to install it on their private computers. They totally could work on toy projects during their time, as the team is in homeoffice a couple a days per week.
I mean the drawback is none as long as they have job security. Unless you realize you work for a public entity that is paid for by the tax payer.
Thank you for attempting to clarify, but it doesn’t seem to me like I misunderstood the first time. Seems you are indeed suggesting they spend their own personal money and hardware for a skill to be used on work time, and that they use their work time for personal projects to ultimately benefit that work time. It seems reasonable to me, and societally positive, that people have the freedom to choose to not do that.
I don’t see how working for a public entity is relevant. If anything, I sure hope (but I’m not deluding myself) the people who work for public entities work slowly, deliberately, and methodically. The last thing I want from public entities is a focus on “velocity” and merging code the authors don’t understand.
10 replies →
What exactly is the skill you acquire by using more AI? If the models get smarter, isnt it a waste of time to get good at the current gen?
I'm probably a worse programmer than I was before I started using frontier AI models, in the sense that I probably have a harder time reading, writing, and debugging code. And I doubt that my knowledge of the AI models themselves will have lasting practical value.
But, because of the explorations I've done with them, I know substantially more about input method APIs, UEFI, PCIDs, seL4, WebAssembly, GLSL, Service Workers, CORS, server-sent events, CSS, content-security policies, memory-hard PBKDFs, Android, numerical integration, Verilog, V8 security, Linux process namespaces, hypervisors with VT-x, multitouch user interface design, radio communications theory, power electronics, TypeScript, physical-layer communications protocols, NTSC video signals, TLA+, bounded model checking, Rust, generative testing, theorem provers, FPGAs, Linux system call overhead, Unix mailbox formats, physical modeling synthesis, damped resonance, KaTeX, geology, dishwashing detergent, microbiology, Cyclone, thermodynamics, X-Windows, localStorage, AVX, Excel, and IndexedDB, for example. Most of these are things I knew very little about before, so I may not know much about then now, but it's enormously more than I did.
Aside from being very pleasurable, I have the impression that this knowledge is valuable in designing systems whose implementation I can then elicit from an AI model.
I don't know how long the knowledge will remain instrumentally valuable. Possibly a year from now, we'll all be dead, or slaves to Sam Altman. Or the AIs will be so much better at designing the systems we would have wanted to design, if we were smarter and knew more, that there's no instrumental value in humans doing it. Or, less drastically, maybe a new AI-written software platform will have so completely displaced Android and the browser platform that there's no value in knowing what they do and don't permit. Like knowing the ins and outs of PHIGS, INFORMIX-ONLINE, or CORBA. (Thermodynamics is probably safe, though.)
But it seems like, in the less insane possible futures, a lot of this knowledge will remain empowering for some time.
I think this comment does a good job of explaining how the breadth of what software engineers do is going to change even more. And again, we are still early. Find a domain to work in!
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The skill of getting familiar with AI use, how to use it, when to use, learning when NOT to use it, is the skill that will land you your next job. Or would you in 2030 expect to hire software devs that never touched AI?
in 2030, there is no need for hiring software devs, or at the very least, we have several times more swes in the world than we actually need.
You get better at building things - asking the right questions at the right time, knowing what to trust and what to look into.
Not very different from managing a team, just without the human problems.
That is a really silly corporate policy - if the actual amount the company wants each employee to spend is maximum €200/mo, $500/mo or whatever then the company should set that as a limit and people will use it.
Saying "you can use as much as you want but don't use too much or you'll get in trouble" is obviously confusing and is going to result in most people barely using it