The post made me think of a different compromise: more public artifacts when we choose, without surrendering our lives to centralized platforms. Like mentioned in the comments, today’s internet is permanent, searchable, and easily weaponized through harassment, surveillance, or data exploitation, so the personal cost of being ‘public’ can be unpredictable and high.
So why don’t we build a system where our identity and activity data live with us by default, on a small server in our home, instead of scattered across company clouds? Everything we do online could be logged locally under our control, and shared only when we explicitly allow it. If a company wants to use our data (for ads, analytics, or training models), it should be a clear opt-in, scoped to a specific purpose, and priced transparently. If it’s valuable, we should get paid for it and that creates incentive structures.
This also matches how I want to use AI personally. I want my own local model that can learn from my data privately, say something like training or updating nightly while I sleep; so I get the benefits of personalization without handing over the raw contents of my life to someone else’s servers. In a world like that, being “more public” becomes a choice you can make safely, not a gamble you’re forced into.
~ organized thoughts with GPT5.2 and used Apple proofread
I usually don’t like it when people use unnecessary big words. But sometimes a word comes by that explains exactly the idea. One of my favorites is Schadenfreude ( it’s funny and real at the same time). When I noticed the author used Solipsism, I definitely judged him for a moment, but after I read the explanation, it was a beautiful description of his stance :)
Solipsism is a philosophical position asserting that only one's own mind is certain to exist.
My experience in trying to build AI tools has always been the 4th way :) Let’s build a coding agent in 2022, procrastination takes over, and then came along Aider, Cursor, Roo, and others. Same with AI observability tools. Wait just enough time to see the tools built themselves.
IMHO, in the software field, learning can be simpler to 2 phases. The first one is exploration, where we read blogs, docs, and books; listen to lectures and talks. Then comes the second phase of exploitation, where we actually use the thing we learned. You can think of all those “learning from scratch” videos as someone who is doing the phase 2. I love the phase one and most of the time don’t have time and energy to sit down and go through the phase 2. Nowadays, I feel like the 2 phases are combined, thanks to LLMs. For instance, I wanted to do some animation for visualizations. This week, I learned AnimeJS by watching CCAgent create the animation I wanted, which was interspersed with questions that were answered with diagrams and text, which accomplishes the phase 1. I do not like letting them run the show. Then comes phase 2, where I organize the code, abstract things, rewrite code, still use their help for long rewrites, but totally my ideas and mine only. This saves time tremendously.
I love the LLM tech and use them everyday for coding. I don’t like calling them AI. We can definitely argue LLMs are not just rearranging code. But let’s look at some evidence that shows otherwise. Last year NYT lawsuit that show llms has memorized most of the news text, you had see those examples. Recent not-yet peer reviewed academic paper “Language Models are Injective and Hence Invertible “ shows llms just memorized training data. Also this https://youtu.be/O7BI4jfEFwA?si=rjAi5KStXfURl65q recent defcon33 talk shows so much ways you can get training data out. Given all these, it’s hard to believe they are intelligently generating code.
So this is the reality we're living in now, where bot farms have become normalized? I always associated bot farms with authoritarian regimes like Russia and China, but are we becoming the same thing? And VC funds are actually backing this? I hope I'm not the only one who finds this completely insane. I can't even listen to the a16z podcast anymore; my mind now permanently associates them with bot farms. These are the news that makes me think does people ever think about moral values and ethics.
Gorilla marketing and bot farms have been around for a very long time. There are bot farms to amplify all sorts of messages. A friend who is a 'performance artest' paid almost nothing to have his linked-in account amplified by a large number of nonsense accounts on that platform. 'creators' frequently buy followers so 'the algorythm' will surface their 'content'. My first roommate 20 years ago almost got a job riding the train and having 'organic' conversations about how great some product is. My solution is to buy nothing and poke and laugh at everything. (Edited for spelling)
I take it as greptile folks know LOC metric is in no way a metric that can be correlated to productivity in LLM era. But putting aside that just knowing how much code is going thru their system seems interesting enough to read the report. Thanks for the dot matrix report.
Most crawlers have no concept of what that is. They will follow links to this site and then follow links out of this site even after being told not to [1]. The majority of crawlers follow zero rules, RFC's, etc... The few platforms that do follow standards and rules are akin to a law abiding citizen in Mos Eisley.
Yes. It's hard to explain the experience of hosting a website since 2023.
A crazy amount of really dumb bots loading every url on the website in a full headless browser, with default Chrome user-agent string. All different ip addresses, various countries and ASNs.
These crawlers are completely automated and simply crawl _everything_ and don't care at all if there's value in what they're crawling or if there's duplicate content, etc.
There's no attempt at efficiency, just blindly crawl the entire internet 24/7. Every page load (1 per second or more?) is from a different ip address.
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