Quite ironic. The original Robin Hood took from the rich and gave to the poor. Robinhood, the app, seems to do the exact opposite: it helps the rich get richer at the expense of regular folk.
> I ended up saying goodbye to those devops folks,
The irony is that "DevOps" was supposed to be a culture and a set of practices, not a job title. The tools that came with it (=Kubernetes) turned out to be so complex that most developers didn't want to deal with them and the DevOps became a siloed role that the movement was trying to eliminate.
That's why I have an ick when someone uses devops as a job title. Just say "System Admin" or "Infrastrcutre Engineer". Admit that you failed to eliminate the siloes.
Enabling Claude Code's sandbox (as OP suggested) does exactly that. It's a system-level filesystem sandbox that only permits access to specified locations for any process, including the python interpreter.
A profitable customer? How would Hetzner know if you're profitable or not?
I've hosted side projects on Hetzner for years and have never experienced anything like that. Do you have any references of projects to which it happened?
this! it favors established business with legal teams and (maybe more importantly) with connections.
The EU is also great at creating a heavy regulatory environment. Which entrenches existing incumbents. So the EU creates barriers that favor big companies, then tries to fix it with grants that... also favor big companies.
And then everyone's surprised that there's no innovation in Europe.
From all the world's companies worth over 100B$ there's only one European company - SAP, founded 50 years ago. [1]
The comment you're replying to is tainted with the survivorship bias. We see successful companies that got government funding, but not the opposite. Maybe we'd have more innovation and competition without government picking these specific winners.
Ironically, one of the companies you mentioned (Apple) now operates in an environment with very little competition and regularly faces antitrust claims.
Government picking winners may actually reduce competition in the long run.
The key difference: when private money picks wrong, it's their loss. When government picks wrong, it's taxpayer money.
> and other than a bit of open source (PyTorch and React are nice, I guess) as far as I can tell it's never really had any mission other than getting big.
I sometimes wonder what motivations these orgs have in contributing to open source.
My cynical side refuses to believe that the reasons are altruistic (although I'm sure there are altruistic individuals in those orgs!).
I think that the decisions to contribute to open source are calculated business decisions made to benefit the organization by:
* Getting outside contributions to the software that's widely used inside an organization
* Getting more people familiar with the software so that when they're hired they are already up to speed
* Attracting talent
* Improving PR
* Undermining competition (Llama?)
Regardless of the reasons, I think that there's a huge net benefit to society from large companies open-sourcing their software. I just don't think that's an argument to view these companies more favorably.
Agree 100%. I noticed that on the Copilot settings page [1] you can switch to Claude Sonnet model (instead of a model trained by Github I assume?). In my experience this improves things.
I use iOS's built in Screen Time settings. For "bad" apps (Reddit, TikTok, etc) and "bad" websites ("hackernews", etc) I set a daily time limit of, let's say, 15 minutes.
I configure a random password for Screen Time so that it's a real hassle to circumvent the daily limit when I get over it.
Yes, you can pre-fill the assistant's response with "```json {" or even "{" and that should increase the likelihood of getting a proper JSON in the response, but it's still not guaranteed. It's not nearly reliable enough for a production use case, even on a bigger (8B) model.
I could recommend using ollama or VLLm inference servers. They support a `response_format="json"` parameter (by implementing grammars on top of the base model). It makes it reliable for a production use, but in my experience the quality of the response decreases slightly when a grammar is applied.
I think in the era of LLMs good docs/FAQ are of an even greater value.
You can write a support bot that sends a user's question + docs/FAQ to an LLM to automatically deal with the basic questions and only involve a human in the loop once a question goes beyond what's in the docs.
I totally understand you, but want to offer a different perspective.
They will also be able to use ChatGPT on the job. And StackOverflow. And Google. If they know how to use tools available to solve a problem, that will benefit them on the job.
If you're testing them for what ChatGPT can already solve, then are the skills being tested worth anything, in this day and age?
Take-home LeetCode, even with cheating will still filter out a good chunk of candidates. Those who are not motivated enough or those who don't even know how to use the available help. You'll still be able to rank those who solved the task. You'll still see the produced code and be able to judge it.
Like other commenter points out, you can always follow up the take-home LeetCode. Usually, it becomes apparent really quickly if a candidate solved it on their own.
A leet-code test would be much more standardized if candidates could solve it at home. Just send me a link to the quiz and let me solve it within a specified time frame.
I've done tests like this for some companies. It felt a lot fairer and more closely resembling the actual work environment than live leet-code interviews, with biased interviewer(s) and a stress factor that's not a part of the actual job.