They're not. It's real world when there's a market for paying Zig jobs, not when you can list a few github repos that use it.
102 karma · joined February 9, 2025
Also, have you tried working instead of twitter? Learning instead of twitter? Just no twitter instead of twitter? Whatever useful thing you're telling yourself that you get from it, good chance that you're wrong and you can do without it completely instead of needing to replace it in some way.
"A purpose of human life, no matter who is controlling it, is to love whoever is around to be loved."
In general, lean body mass loss is more of a result of rapid weight loss (I certainly consider mine very rapid), than result of the medication itself. If I was able to lose the same weight in the same period of time without the medication, and kept my protein and resistance training the same, I'd expect a similar ratio of muscle/fat loss.
Overall extremely happy with the outcome, very grateful that these drugs exist and that I was able to access them.
2. Break things down into small tasks
3. Checklists for all tasks, preferably on paper, crossing things out feels nice
4. Work surrounded by people, I need the accountability of being observed. Go to the office more often, use Focusmate where you pair with strangers, or even open an empty video call with just yourself and have yourself on camera on one screen.
5. In general look for environments that give frequent feedback, as frequent as possible. That's why long things and big projects need to be broken down.
6. Noise cancelling headphones, repetitive music with a nice beat and no lyrics.
7. But the main that unlocked everything was the medication, without it the rest of the tips don't do much.
These look like positive changes, a 2x longer event isn't 2x more fun or 2x more satisfying to participate in.
After skipping the past couple of years, I feel like I'm more likely to give it a go again this year.
They are but they have nothing to do with how frequent anything is in literature which was your main point.
At some point people got this idea that LLMs just repeat or imitate their training data, and that’s completely false for today’s models.
Even if you only change your commands to 'uv venv ...' and 'uv pip install ...' and keep the rest of your workflow, you'll get
1. Much faster installs.
2. The option to specify the python version in the venv creation instead of having to manage multiple Python versions in some other way.
No pyproject.toml, no new commands to learn. It still seems like a win to me.
Why didn't the fact that Redis already existed make the whole thing feel pointless before? You could just go to github and copy the thing. I don't get why AI is any different in this regard.
To get it done correctly, that's always what it's been about.
I don't feel that code I write without assistance is mine, or some kind of achievement to be proud of, or something that inflates my own sense of how smart I am. So when some of the process is replaced by AI, there isn't anything in me that can be hurt by that, none of this is mine and it never was.
This isn't accurate.
> So I feel pressure to always, always, start by info dumping the problem description to AI and gamble for a one-shot. Voice transcription for 10 minutes, hit send, hope I get something first try, if not hope I can iterate until something works.
These things have planning modes - you can iterate on a plan all you want, make changes when ready, make changes one at a time etc. I don't know if the "pressure" is your own psychological block or you just haven't considered that you can use these tools differently.
Whether it feels satisfying or not - that's a personal thing, some people will like it, some won't. But what you're describing is just not using your tools correctly.
More like $115 billion based on your own link. The $1T is a guess based on promises made, far from "needs to spend that much just to exist".
Spending $30 billion a year doesn't sound that apocalyptic.
2. Overall market dynamics still apply - the increase from 1. is relative to the market i.e. if the market has been tough for other roles like frontend for example, it has been less tough for MLEs because they work on the thing that's exciting at the moment.
3. Should new grads focus on it? New grads will likely have a difficult time regardless of what they decide to do - maybe in a couple of years there won't be excitement around AI/ML, maybe there will be more, maybe something else will be hot. The overall market almost certainly be different, and that could be for the better or worse.
Hard to predict the future. Whatever you decide to do early in your career, know that you're not married to it forever. Develop general skills that can be applied in many areas.
Why do some people insist on screaming about this from the rooftops?
I also have ADHD and a lot of this matches Dr Russell A Barkley's description of ADHD, particularly when he describes it as a performance and executive function disorder - https://www.youtube.com/playlist?list=PLzBixSjmbc8eFl6UX5_wW.... ADHD includes much more but this "slow thinking" seems to be a prominent feature.
We really don't need to assign ROI to every single thing we do.
And I don't think comment culture takes away from any of the activites that lead to more meaningful relationships. Like, how do you imagine this works - "I'm not going to comment on this tech blog post while I'm having my cofee this morning so that later this week I can meet with people at a local book club"? One has nothing to do with the other.
That's a nice balance for me - it leaves more options than completely blocking it but it protects me from being bounced around by the algorithm.