Meaning, what you ask for (or how expensive you are perceived, if you have that strong resumee) for the industry you apply, may be too different and leading to limited access.

Sometimes I feel junior people have it easier (I felt like I did, personally) since the expense in salary is pretty limited compared to either other roles or more senior people

If you don't need this features, specially the distributed one, going tall (single instance with high capacity, replicate when necessary) or going simpler (multiple servers but without spark coordinating the work) could be good options depending on your/the team's knowledge

What about Gitlab instead of GitHub, is there an equivalent to cursor 1.0 product?

What is working for me right now is noting everything in a calendar so I cannot forget it or as TODO in a somewhat heavy personalized Obsidian configuration.

A few years ago (5-6 aprox) I started copying my older co-workers habits to see myself improve. Physical notebooks were soon discarded because I never remember where I wrote down things.

I used a TODO plugin in sublime which worked for several months, until I felt I needed screenshots so I moved to OneNote. After a while I became frustrated with not being able to customize it enough, so I started trying out different things. I saw a coworker using Obsidian, watched a couple long YouTube videos to learn how to customize, and I'm never going back.

My team this week told me they are impressed with how much info I write down and it was a very proud moment for me!

Would it be correct to understand this as a syllabus, and not the actual explanations/lecture/content?

I have realized I can give so many tips and reference so many great content online to learn math, programming, engineering... But find myself missing anything about managing

For me, what's missing is intent. Most of the time I feel I could be doing better, I stop and think: wait, this is my resting time. Or, wait, this is my hobby. I feel even though I fall in one end of the balance, many times this articles fall in the other.

If I tried to deep dive and study as much as is suggested, I'd have no energy for other things that I value more right now. Reading author articles it seems to me others have different energy or their effort is focused differently, but I'm always cautious because burning out it's not something I want to ever repeat

And it adds nothing. I'm sorry but saying "Whether that content is used to train a human mind or an artificial one is probably not up to you" may be worse than saying nothing at all.

First because it shows enough doubt on whether it's up to the authors of content (IP laws, fair use, intent of the use, and many things I ignore), while giving no laws as an example or frame of reference.

And second because it's comparing a human mind that we know exist, to an artificial one, which implies:

1. An LLM is an artificial mind, or close to one, whatever that is (again, not defined).

2. If they were to exist, they would be both equivalent and treated the same as a human one.

The amount of jumps in a couple sentences, added to the uncertainty of how copyright would/will work, multiplied by the numer of times I/we read that type of comment every single time, it's getting tiresome. And it's adding noise to the noise-signal ratio.

I think there is a problem when someone with such proclaimed knowledge of the sector gets to this, and similar, pieces of data, and does not attribute it to pricing. Could it be queries are short because bigquery pricing for analysis, as confusing as this models are, is based on amount of data?[0]

Because the other line of reasoning is that a big chunk of that 90% of professionals being paid to do their jobs, do NOT take into account pricing of the tool and are using it for small data, instead of thinking that people are using the best tool with the lowest price, because there's plenty of options to process and analyse data right now in the cloud.

On the "business have low amount of data", that matches my experience as well. At first I thought I was simply dealing with smaller sized companies, but it's a trend of doing big data projects for data that'd fit a pendrive.

[0] https://cloud.google.com/bigquery/pricing#analysis_pricing_m...