I haven't got to 10m yet, but I saved 70-80% of my take home pay since ~2008 and I have enough to quit at any time and live the rest of my life without working. That is just by investing in the 3-fund portfolio and without the crazy SF salaries.
Before Covid, I lived on about 25K a year since I had a paid off condo then. Now, I am renting and live on around 36K a year. I realize my situation doesn't work for everyone. Some people cannot fathom not buying a new phone and computer every year and a new car every 3 years.
Also, now, I am fully working from home so that helps with saving on gas and not eating out as much. I make my coffee every morning instead of Starbucks on the way to work and I make my own lunch and dinner 95% of the time.
No kids, rent is $1800 a month for a 1 bedroom. I could rent the same for cheaper but I like this place. I'm in Washington State, Software Devs make decent money where I am but not SF wages. I make good money but nowhere near the top. I have an easy job, WFH and rarely work over 40 a week.
Being FI helped me out greatly in December 2020 when My company laid off half of my team and expected me to take on double the load, including lots of extra after hours on-call support. I had a pretty great time not working for ~3 years during Covid. However, I am back to work after an old friend and boss offered me a WFH job that I couldn't refuse. He has since retired so I will stick around until current management pisses me off again, they downsize me or I just get sick of logging into teams/outlook at 7AM every morning.
Not the exact same problem, but a few months ago, I tried to block youtube traffic from my home (I was writing a parental app for my child) by IP. After a few hours of trying to collect IPs, I gave up, realizing that YouTube was dynamically load-balanced across millions of IPs, some of which also served traffic from other Google services I didn't want to block.
I wouldn't be surprised if it was the same with LLMs. Millions of workers allocated dynamically on AWS, with varying IPs.
In my specific case, as I was dealing with browser-initiated traffic, I wrote a Firefox add-on instead. No such shortcut for web servers, though.
I did that, but my router doesn't offer a documented API (or even a ssh access) that I can use to reprogram DNS blocks dynamically. I wanted to stop YouTube only during homework hours, so enabling/disabling it a few times per day quickly became tiresome.
Your router almost certainly lets you assign a DNS instead of using whatever your ISP sends down so you set it to an internal device running your DNS.
Your DNS mostly passes lookup requests but during homework time, when there's a request for the ip for "www.youtube.com" it returns the ip of your choice instead of the actual one. The domain's TTL is 5 minutes.
Or don't, technical solutions to social problems are of limited value.
I think dnsmasq plus a cron on a server of your choice will do this pretty easily. With an LLM you could set this up in less than 15 minutes if you already have a server somewhere (even one in the home).
In this case, I don't have a server I can conveniently use as DNS. Plus I wanted to also control the launching of some binaries, so that would considerably complicate the architecture.
Yes, my kid has ADHD. The browser add-on does the job at slowing down the impulse of going to YouTube (and a few online gaming sites) during homework hours.
I've deployed the same one for me, but setup for Reddit during work hours.
Both of us know how to get around the add-on. It's not particularly hard. But since Firefox is the primary browser for both of us, it does the trick.
They rely on residential proxies powered by botnets — often built by compromising IoT devices (see: https://krebsonsecurity.com/2025/10/aisuru-botnet-shifts-fro... ). In other words, many AI startups — along with the corporations and VC funds backing them — are indirectly financing criminal botnets.
You cannot block LLM crawlers by IP address, because some of them use residential proxies. Source: 1) a friend admins a slightly popular site and has decent bot detection heuristics, 2) just Google “residential proxy LLM”, they are not exactly hiding. Strip-mining original intellectual property for commercial usage is big business.
How does this work? Why would people let randos use their home internet connections? I googled it but the companies selling these services are not exactly forthcoming on how they obtained their "millions of residential IP addresses".
Are these botnets? Are AI companies mass-funding criminal malware companies?
>Are these botnets? Are AI companies mass-funding criminal malware companies?
Without a doubt some of them are botnets. AI companies got their initial foothold by violating copyright en masse with pirated textbook dumps for training data, and whatnot. Why should they suddenly develop scruples now?
It used to be Hola VPN which would let you use someone else’s connection and in the same way someone could use yours which was communicated transparently, that same hola client would also route business users. Im sure many other free VPN clients do the same thing nowadays.
so user either has a malware proxy running requests without being noticed or voluntarily signed up as a proxy to make extra $ off their home connection. Either way I dont care if their IP is blocked. Only problem is if users behind CGNAT get their IP blocked then legitimate users may later be blocked.
edit: ah yes another person above mentioned VPN's thats a good possibility, also another vector is users on mobile can sell their extra data that they dont use to 3rd parties. probably many more ways to acquire endpoints.
“Known IP addresses” to me implies an infrequently changing list of large datacenter ranges. Maintaining a dynamic list (along with any metadata required for throttling purposes) of individual IPs is a different undertaking with higher level of effort.
Of course, if you don’t care about affecting genuine users then it is much simpler. One could say it’s collateral damage and show a message suggesting to boycott companies and/or business practices that prompted these measures.
Nail guns are great because they're instant and consistent. You point, you shoot, and you've unimpeachably bonded two bits of wood.
For non-trivial tasks, AI is neither of those. Anything you do with AI needs to be carefully reviewed to correct hallucinations and incorporate it into your mental model of the codebase. You point, you shoot, and that's just the first 10-20% of the effort you need to move past this piece of code. Some people like this tradeoff, and fair enough, but that's nothing like a nailgun.
For trivial tasks, AI is barely worth the effort of prompting. If I really hated typing `if err != nil { return nil, fmt.Errorf("doing x: %w", err) }` so much, I'd make it an editor snippet or macro.
> Nail guns are great because they're instant and consistent. You point, you shoot, and you've unimpeachably bonded two bits of wood.
You missed it.
If I give a random person off the street a nail gun, circular saw and a stack of wood are they going to do a better job building something than a carpenter with a hammer and hand saw?
> Anything you do with AI needs to be carefully reviewed
Yes, and so does a JR engineer, so do your peers, so do you. Are you not doing code reviews?
> If I give a random person off the street a nail gun, circular saw and a stack of wood
If this is meant to be an analogy for AI, it doesn't make sense. We've seen what happens when random people off the street try to vibe-code applications. They consistently get hacked.
> Yes, and so does a JR engineer
Any junior dev who consistently wrote code like an AI model and did not improve with feedback would get fired.
You are responsible for the AI code you check in. It's your reputation on the line. If people felt the need to assume that much responsibility for all code they review, they'd insist on writing it themselves instead.
> there is a large contingent of the Go community that has a rather strong reaction to AI/ML/LLM generated code at any level.
This Go community that you speak of isn't bothered by writing the boilerplate themselves in the first place, though. For everyone else the LLMs provide.
Well that may also be because ChatGPT is worse than Gemini and Claude for coding. I don't know what the benchmarks say, I am just saying that from my own experience.
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