SpookyMulder

Not to be That Guy, but with kindness I offer a small correction: "out away" -> "outweigh".

Exactly this. I doubt the effectiveness of a measure like this. Without enforcement, explicit and public cooperation from AI scrapers, consequences/accountability, and legal backing, it's just theater.

The equivalent of a strongly worded letter.

It's complementary to robots.txt.

• It's weird that it's XML, in 2025.
• It's weird that it doesn't use the .well-known/ prefix which has trended in the last decade for placement of files like this.
• It's weird that it canonically uses the generic "license.xml" file name instead of "license.rsl" or "rsl.xml" or something that more clearly indicates its semantics.

But I do like the idea of having some widely adopted conventional way of expressing, in unambiguous terms, which usages are expressly prohibited, and that AI training is among them.

Good luck finding someone with all those qualifications, with at least three projects that meet all the criteria in their portfolio, and willing to work in NY for $100k. The caliber of candidate they seem to be looking for is easily worth over twice that.

That said, the market is full of desperate job-seekers who might take the bait.

To me, the single biggest argument against LLMs and generative AI is this:

It is a technology whose sole purpose, by design, is to persuade humans to accept what it has produced, with no regard for correctness. Bottom line, that's mechanically how the technology works. An automated grifter, thief, liar, and manipulator.

And it's so disturbingly effective and in widespread use that our very sense of reality and truth under attack.

The way this comment is written doesn't sound anything like the OP or the GitHub issue. Different tone, different dialect/spelling... lot of linguistic red flags. Not that I'm judging either way, it's just suspicious how vastly different they are.

Are the release notes AI generated? It reads like it.

In years past, I've used Elasticsearch and Kibana. The learning curve is steep and the system resource requirements warrant a dedicated machine, but once you get it dialed, it's really effective as a centralized logging server.

Prometheus and Grafana are for time-series data (metrics), not logs. If you're already getting that from netdata, don't bother with these, as they'd be redundant with what you have.

syslog is about as idiomatic as it gets for log management in linux, but i don't have enough experience using it effectively to give any pointers there. If you don't really know what you want, yet, and just want to collect logs from all the things and see them in one place so you can begin to try and make sense of them and make refinements from there, then syslog seems like an excellent place to start.

Occam's Razor: coincidence is the most likely explanation. Most of us aren't as unique as we think we are. It doesn't take very long for a keen observer (or algorithm) to profile our behavior based on direct surveillance.

Think of it this way: if you were the algorithm and were looking at a detailed account of every second of time you spent on the platform, and also had the same accounting for every other user... what inferences and connections might you, the algorithm, be able to make about you, the person?

It's a feature, not a bug, for platforms to recommend relevant content. It's also intrinsic for you to engage with the platform authentically, engaging with it in a way that aligns with your interests, preferences, and demeanor. Relevant content drives engagement. Engagement drives revenue. Irrelevant content does the opposite and serves to benefit no one involved. The popular platforms blew up exactly because they are so good at knowing what you want to see even before you do.

In short: no amount of tech can save us from ourselves.

As someone who was recently fired for, among other things, being a stick in the mud about AI, I have some thoughts.

Try not to take work too seriously.

I drew a picture of Carl from Aqua Teen Hunger Force saying, "It don't matter. None of this matters." and put that by my monitor in my office. Whenever I started to feel activated about some bullshit, I just glanced over at Carl. It calmed me down to be reminded that my real job is to simply not lose the job.

It's a very bad time to be unemployed and anti-AI right now. Just tread lightly, ride out the storm, and let the inevitable reckoning eventually come to pass.

RE autoscaling: effective distributed systems design isn't really language-dependent. Java apps can scale just as well as ones written in Go. That said, I can see there being a case for Java apps not making it as easy to build that way. There's definitely a lot of mainframe/monolith-oriented patterns in both the standard library and in enterprise Java culture.

As for the job market and career investment, I'd say this:

• Keep investing more deeply in what you're good at. That's your foundation and what sets you apart.
• Avoid chasing the "next big thing" based on speculation and trends alone.
• The next step in your career hinges more on your ability to think and design at higher levels than it does on lateral moves to another programming language.
• Explore languages and technology that you think are interesting, relevant, or can provide value or elevate what you're already doing. The main benefit of doing this is to engage your brain differently and encourage change, improvement, and growth. This will indirectly improve your work and help your career.

I've written a lot of Java in my career and studied it in college, and I've written one app professionally and several hobby projects and utilities in Go. There's a lot to like about it, regardless of its marketability on a resume.