u/Witty_County5128

Hey everyone, hope you're all doing well.

So a bit about me, I'm 21, studying CS, live in a developing country. I've always wanted to actually build wealth, not just talk about it, but I don't really know where to start in a practical way.

I still live with my parents, they cover like 90% of my expenses. We're middle class, not rich but comfortable. I'm grateful for that but I really want to get to a point where I'm not depending on them anymore.

I guess what I'm asking is, for people who actually built something from not much, what did you do first? Did you save aggressively, learn some skill that paid off, start a side hustle, get into investing early? I have a technical background but basically no capital, and honestly the currency/economy situation where I live makes saving or investing harder than if I was in the US or Europe.

If you were starting over in your early 20s with not much money but some time and skills, what would you actually do first? And is there anything you wish someone told you back then instead of you having to learn it the hard way?

Appreciate any real answers

Hey everyone, hope you're all doing well.

So a bit about me, I'm 21, studying CS, live in a developing country. I've always wanted to actually build wealth, not just talk about it, but I don't really know where to start in a practical way.

I still live with my parents, they cover like 90% of my expenses. We're middle class, not rich but comfortable. I'm grateful for that but I really want to get to a point where I'm not depending on them anymore.

I guess what I'm asking is, for people who actually built something from not much, what did you do first? Did you save aggressively, learn some skill that paid off, start a side hustle, get into investing early? I have a technical background but basically no capital, and honestly the currency/economy situation where I live makes saving or investing harder than if I was in the US or Europe.

If you were starting over in your early 20s with not much money but some time and skills, what would you actually do first? And is there anything you wish someone told you back then instead of you having to learn it the hard way?

Appreciate any real answers

Over the past year, frontier AI models have improved much faster than I expected. Features that felt state-of-the-art a few months ago are now becoming the baseline.

Do you think Fable will still feel competitive a few months from now, or will AI progress make it seem outdated faster than expected? What do you think will matter most for staying competitive?

from what i've read, recent frontier llms seem to use broadly similar transformer architectures, while many of the visible improvements (reasoning, coding, and agentic behavior) appear to come from post-training techniques such as supervised fine-tuning, RL, preference optimization, and tool-use training.

at the same time, labs continue to spend enormous compute on pretraining with larger, higher-quality datasets, so i assume pretraining is still doing most of the heavy lifting.

is there any research, ablation study, or industry experience that sheds light on how much each stage contributes to recent capability gains? is there a growing consensus that post-training is now the main differentiator between frontier models, or is pretraining still responsible for most of the improvements?

from what i've read, recent frontier llms seem to use broadly similar transformer architectures, while many of the visible improvements (reasoning, coding, and agentic behavior) appear to come from post-training techniques such as supervised fine-tuning, RL, preference optimization, and tool-use training.

at the same time, labs continue to spend enormous compute on pretraining with larger, higher-quality datasets, so i assume pretraining is still doing most of the heavy lifting.

is there any research, ablation study, or industry experience that sheds light on how much each stage contributes to recent capability gains? is there a growing consensus that post-training is now the main differentiator between frontier models, or is pretraining still responsible for most of the improvements?