Ha! This is great. I've been waiting for someone to make this.
Giving an LLM a computer makes it way more powerful, giving it a kubernetes cluster should extend that power much further and naturally fits well with the way LLMs work.
I think this abstraction can scale for a good long while. Past this what do you give the agent? Control of a whole Data Center I guess.
I'm not sure if it will replace openclaw all together since kubernetes is kind of niche and scary to a lot of people. But I bet for the most sophisticated builders this will become quite popular, and who knows maybe far beyond that cohort too.
I don't like the premise of this game. If you're autistic, don't mask. Live authentically as yourself and find people who love you for who you are.
You'll annoy the hell out of some people, and thats fine. They can find other people to spend time with.
You can probably find a good community where you are, and if not just move to SF which is something like the autism homeland. Being autistic there is valorized and even imitated in sort of amusing ways.
Masking is a kind of hell, living someone else's life. Unmasking and living as yourself feels scary at first but the people who will love you that way can only find you if you live that way.
There is a funny parallel I see with Kubernetes that I also saw a lot with Linux in the early years. There are thousands of packages and tools you can install on Linux (think phpmyadmin for example) and new users sometimes go wild installing every single package they read about.
After a while, the more mature Linux engineers start going the other way. Ripping out as much as possible. Stripping down to the leanest build they can, for performance but also to reduce attack surface and overall complexity.
Very similar dynamic with k8s. Early days are often about scooping up every CNCF project like you're on a shopping spree. Eventually people get to shipping slim clusters running and 30mb containers with alpine or nix. Using it essentially as open source clustering for Linux.
For sure. It's been amazing honestly and I feel like it has really accelerated my learning. Enough that I'm trying to get really serious about making the most out of this new leverage seemingly out of nowhere.
I use it a lot for mapping out of the initial concepts but I find one of the best use cases is after understanding the basics, explaining where I need to learn more and asking for a book recommendation. The quality of my reading list has gone up 10x this way and I find myself working through multiple books a week.
Great for code too obviously, though still feels like early days there to me.
Building using LFS has been on my list of "I really should probably do that just to learn" for about 20 years now. I'll get around to it! This year I'm finally learning Lisp (and really enjoying it).
Really cool idea. Novel, I imagine a lot of people would play this. I would suggest a social media campaign with short form videos. Seems like something that has the potential to go viral or at least make a lot of money.
It's not a public market so nobody knows how much you're making if you sell, but if you look at current valuations it must be a lot.
In that context, it would be quite hard not to leave and sell or stay and sell. What if oai loses the lead? What if open source wins? Keeping the stock seems like the actual hard thing to me and I expect to see many others leave (like early googlers or Facebook employees)
Sure it's worth more if you hang on to it, but many think "how many hundreds of M's do I actually need? Better to derisk and sell"
Fortunately big tech jobs are available in EU too. Highest salaries might trickier without moving to US, shouldn't be too hard to transfer to US once you get a job at one if you want to. Making quite a high salary without moving is possible too (though still need to be a in a major metro that has big tech companies.)
This is fairly straightforward imo. Most money is in big tech. Look at levels.fyi to get an idea of the roadmap.
Big tech hires mostly off leetcodes. There are other factors too.
Your journey begins with practicing leetcodes and reading all the books on teachyourselfcs.com
Study dilligently. Watch YouTube courses too but this should be considered supplemental.
Apply for big tech jobs. This will probably take several trys, especially in this market. Just keep applying and studying.
Once you're at a big tech company keep studying, learn from the smartest people you meet, and ship a lot. After a promotion or two apply to Meta (or someone else if they're paying more on levels.fyi at that point, but Meta pays especially well)
Start giving presentations at conferences. At higher levels in big tech this is encouraged and sometimes even expected as part of promo packets. Also practice your writing. Starting on writing a technical book on a subject your an expert in by this time would be good.
Keep shipping, keep learning, keep getting promoted. Once you're on that track you're well on your way to $1M/yr TC.
I'm not sure why but it seems like most of the high quality AI content is on twitter. On average seems to be around ~4 months ahead of HN on AI dev approaches.
I would suggest following / reading people who talk about using Claude 3.5 sonnet.
Lots of people developing whole apps using 3.5 sonnet and sometimes cursor or another editor integration. The models are getting quite good now at writing code once you learn how to use them right and don't use the incorrect LLMs (a problem I often see in places other than twitter unfortunately.) They seem to get better almost weekly now too. Just yesterday Anthropic released an update where you can now store your entire codebase to call as part of the prompt at 90% token discount. Should make an already very good model much better.
Gumroad's CEO has also made some good YouTube content describing a lot of these techniques, but they're livestreams so there is a lot of dead air.
This is a bit of a Zen thing you're describing. A lot of different approaches and theories on getting to the same thing here I would say. It's hard to think of specific advice here beyond "just start doing it" which does not seem very helpful. Maybe a good insight here is "practice will make it easier."
I think ultimately for me this mindset was cultivated at a pretty young age with some writing and art I happened to come across. I love content like that and seek it out now. I think you can become more and more growth mindset oriented with time. I'll share some of the things I've liked on the topic here, maybe that will be useful:
This book is so good. It's about building early computers but it feels just like tech does today in the way it's described. Which make it feel like this bigger context you're reading into. That even before computers were mainstream, there were still those who tinkered.
Two things are especially memorable to me. One is a casual remark in the book that they found the best way to get things done is to pair someone very experienced and cynical with someone very inexperienced and naive. Combined they would get lots done together compared to either alone. I think this is still true today.
The other thing is the intro. It's about the head of the project getting a group together and renting a sailboat on vacation. On the sailboat the get tossed and at times feel like they barely survived and it ends with someone saying "if this was his vacation...what did this man do for fun!?"
If an API is exposed you can just have the LLM write something against that.