I think its a good approach to discover and build upon what feels good. There are plenty of pianists that can play a catalogue of songs, or improvise "flawlessly", but rareness or uniqueness are great qualities for art to have.

I'm not sure how well the same applies to work, though, where fulfilling implicit or explicit standards plays more of a role. A developed "taste" plays a role in doing e.g. a good sysadmin job, but if you're creating something unique here, any successor is likely to have a bad time, no matter how beautiful this creation seemed at the time.

I do agree with the idea that passion can be a big driver in both worlds, it just seems to me that in work there's more to gain if it is harnessed to some degree.

But yeah, I would also like these two minutes of my life back.

Well, as someone who has also generated some text with LLMs, at least I learned that it's still possible to generate truly excruciating stuff with the "right" model and prompt.

Addressing the wider point, yes, there is still a market for great artists and creators, but it's nowhere near large enough to accommodate the many, many people who used to make a modest living, doing these small, okay-ish things, occasionally injecting a bit of love into them, as much as they could under time constraints.

Perhaps there is a future where individuals can translate large numbers of libraries, and instead of manually porting future improvements of the original versions to the copies, just rerun the translation as needed.

What makes a huge difference here is the ease and speed. I recently did a similar analysis of my HN posts. I have hundreds of posts, and it took like 30 seconds with high quality results. Achieving this quality level would have taken me hours, and I have some relevant experience.

This certainly opens up some new possibilities - good ones like self-understanding, potentially ambiguous ones in areas such as HR, and clearly dystopian ones ...

But perhaps the more important filtering is on quantity as opposed to neutrality? Perhaps filtering out a large amount of news, even with some bias, is the lesser evil, as compared to news outlets that depend on stirring the emotions of their readers every single day?

Wikinews used to be okay in this regard, but the German version I used has died down a bit, and the English one is even more centered on the Anglosphere than HN.

Is that too much non-tech? Or are the tech posts not news-like enough? Or do you dislike side-tracks in the discussions?

I guess hardly anyone outside the US uses Truth Social, so that alone could perhaps explain the different impact of a US event on traffic. Or is there also a lack of organic baseline activity on Truth Social, and people only go there to read Trump's posts?

In other cases, like software development, there is a split between tasks of a narrow scope and those of a wide scope. Creating one-shot pieces of software is kind of a solved issue now. Maintaining some relatively self-contained piece of software might soon turn into a task for single maintainers that review AI PRs. The more the bottleneck is context tracking, as opposed to producing code, the less useful the AI. I am uncertain, however, how the millions of devs in the world are distributed on this continuum.

I am also skeptical about legal protections or unionization, as many of these jobs are quite suited to international competition.

https://en.m.wikipedia.org/wiki/Gadsby_(novel)

https://en.m.wikipedia.org/wiki/PC_System_Design_Guide#Color...

> 762 vs 20k hits

That's impressive! I guess the difference is smaller here in Berlin as we have a lot of rails shops, but internationally speaking, your stat might well be representative. There might also be less competition in the Ruby job market, but perhaps not to such a degree to offset the difference in job numbers.

In the end, Python is probably the safer and more career friendly option, especially if you're interested in AI. However, if you enjoy coding, Ruby is IMHO the top choice to maximize this enjoyment. I don't think it's the second coming, but there's no other commonly used language where you can do things as easily and so without bending to any limits of the language. The downside of this power is that you're never done learning about it. Maybe people who are drawn to coding as a hobby are more likely to enjoy Ruby than those with more of a separation between work and private interests.

But I'd be interested to know where Python is more useful, apart from science, data science, ML, AI, and such.