-
28 votes
-
Anticipating a world where LLM use is widespread
16 votes -
Gyre
15 votes -
Claude Code's source code leaked
50 votes -
The cognitive dark forest
31 votes -
A.T.L.A.S: outperform Claude Sonnet with a 14B local model and RTX 5060 Ti
43 votes -
Sycophantic AI decreases prosocial intentions and promotes dependence
31 votes -
Google’s TurboQuant AI-compression algorithm can reduce LLM memory usage by 6x
44 votes -
cq: Stack Overflow for agents
15 votes -
Anthropic takes legal action against OpenCode
19 votes -
I hope you don't use generative AI - an essay about my experience offering an open-source tool
71 votes -
Executing programs inside transformers with exponentially faster inference
14 votes -
Can coding agents relicense open source through a “clean room” implementation of code?
51 votes -
The future of AI
15 votes -
GNU and the AI reimplementations
23 votes -
A "Real BMO" local AI Agent with a Raspberry Pi and Ollama
17 votes -
Electricity use of AI coding agents
29 votes -
Is it worthwhile to run local LLMs for coding today?
I've made the decision to purchase a new M5 Macbook Air because of the memorypocalypse. My current M1 model is already upgraded to the amount of memory and storage as the current base model and...
I've made the decision to purchase a new M5 Macbook Air because of the memorypocalypse. My current M1 model is already upgraded to the amount of memory and storage as the current base model and I'm wondering if it's worth spending the extra 2-4 hundred dollars on memory upgrades today.
My current computer is more than good enough for today but I figure I should probably future proof just in case. I was thinking the 16GB would be enough, but I also know that I'm kind of falling behind by not embracing AI coding agents. According to my research the maximum 32GB is recommended for most coding-relevant models - almost as a minimum.
I work in education so coding is not actually much of a need, and obviously there are cloud providers I could use if I end up needing them in the future. I also have less than a teacher's salary because I work part time, which is the greatest reason why I'm sticking with the 16GB base for the moment, but other than that I also don't do many memory-intensive programs. But I thought I would get some recommendations before they start shipping.
I'd also be interested on people's opinions on trading in my old one, since it'll only get me ~$275 back. I'm considering reneging on that part and keeping it around to act as a web server or give it to my husband who has a computer that still runs Windows 7 and barely uses it.
35 votes -
Hacker used Anthropic's Claude chatbot to attack multiple government agencies in Mexico
21 votes -
Eval awareness in Claude Opus 4.6’s BrowseComp performance
14 votes -
An AI agent published a hit piece on me
49 votes -
LLMs can unmask pseudonymous users at scale with surprising accuracy
44 votes -
My personal AI assistant project
Let me start off by saying that I'm exhausted by AI hype. Being interested in LLM agent technology (AI agent hereafter for brevity) means skimming over a lot of hype for one or two useful, semi...
Let me start off by saying that I'm exhausted by AI hype. Being interested in LLM agent technology (AI agent hereafter for brevity) means skimming over a lot of hype for one or two useful, semi reality based, bits of information. Maybe the part that I find the most frustrating is how effective the hype is. I don't know if there's ever been a hype cycle like this. Probably a big part of the reason for that is the internet has already proven, within living memory for most people, that technological revolutions really can change everything. Or mess everything up. Either way they generate a lot of economic activity.
So this post is not that. I'm not going to tell you about how AI agents are the second coming for Christ. I'm not selling anything.
Fairly early into learning about AI agents I wanted a way to connect to the agent remotely without hosting it somewhere or exposing ports to the internet. I settled on tailscale and a remote terminal and moved on, I rarely used it. Somehow the tiny friction of "Turn on tailscale, open terminal app, connect, run agent" was enough to make it not feel worth it.
I know I'm far from the only person who had the same "I want it remote" thought, the best evidence: OpenClaw. It's just one of those things that everyone naturally converges on.
If you're not familiar with OpenClaw, the TLDR is: Former founder with more money than he'll ever need vibecodes a bridge between instant messenger apps and LLM APIs. Nothing about it is technically challenging or requires solving any particularly hard problems. It almost immediately becomes the fastest growing GitHub repo of all time and is currently at number 14 for number of stars. It blew up the (tech) internet like very few things ever have. Within months he was hired by Open AI.
OpenClaw now does more than just connect messaging and agents, but I believe that one piece is the killer feature. My tailscale terminal solution, combined with a scheduled task or a cron job and some context files could already do all of the things that OpenClaw can do, and countless people had already implemented similar solutions. But I think it was the tiny bit of friction OpenClaw removed that was responsible for a lot its popularity.
I thought that was interesting but I have no interest in the security nightmare that is OpenClaw, or the "sentience" vibe for that matter, so I built my own tool.
Essentially it's just a light secondary harness combined with a bridge between Signal and Claude Code. It does some other things too, things I wished existing harnesses did, some memory and guidelines, automated prompts and reminders to wake the agent up and have it do stuff, some context to give the agent some level of persistence, make it less LLMy, less annoying. None of that is particularly interesting though.
Once I got it working (MVP took less than a day) and started playing with it, the OpenClaw phenomenon made a lot more sense. Somehow having the agent in a chat interface, with almost zero friction (just open the chat and send something) was cooler than it had any reason to be.
I can't explain it any better than that at the moment. Not only was it kinda fun, it lent itself to a whole range of "what ifs". What if it could do X? What if I wrote a tool that gave it Y capability? I've been experiencing that for some time, but somehow agent in your pocket has a different feeling.
Here's an example of a "what if". What if it could do our grocery shopping? I definitely want that. I already had a custom browser tool that I built for agent coding assistance so I was most of the way there. It was just a matter of teaching the agent to login and navigate a website, something they're already trained to do. Some hand holding, a few helper scripts, and an evening's worth of hours later and I had it working. The agent can respond to a shopping request by building a shopping list based on our most recent orders, presenting it to us for approval/edits in a Signal group chat, doing searches for any additional product requests and adding the finalized order to the cart. It could also checkout the order and schedule the delivery time but I'm doing the last 2 clicks manually for the time being. It's an idiot savant, it seems like a bad idea to give it access to my credit card. Maybe eventually.
The fact that I can handle shopping with a couple of signal messages feels effortless in a way that handling shopping by connecting to my PC terminal remotely via tailscale terminal wouldn't have. Especially when I can include people in the loop who have no interest in tailscaling anywhere. Everyone can use messaging apps.
I imagine before long solutions like this will be built in, either in the grocery websites and apps, or into the frontier harnesses themselves. There will probably be agents everywhere, for better or worse. Probably I'll wish that the agents would all fuck off. In the meantime it's exciting how easy it is to get these tools to do useful things.
33 votes -
microgpt - GPT in 200 lines
32 votes -
AI’s memorization crisis
24 votes -
Anthropic rejects latest US Pentagon offer: ‘We cannot in good conscience accede to their request’
61 votes -
New accounts on Hacker News ten times more likely to use em-dashes
54 votes -
Updating Eagleson's Law in the age of agentic AI
Eagleson's Law states "Any code of your own that you haven't looked at for six or more months might as well have been written by someone else." I keep reading how fewer and fewer of the brightest...
Eagleson's Law states
"Any code of your own that you haven't looked at for six or more months might as well have been written by someone else."
I keep reading how fewer and fewer of the brightest developers are writing code and letting their AI agent to do it all. How do they know what's really happening? Does it matter anymore?
Curious to hear this communities thoughts
11 votes -
Ladybird chooses Rust as its successor language to C++, with help from AI
33 votes -
The Claude C Compiler: what it reveals about the future of software
16 votes -
Why doesn’t Anthropic use Claude to make a good Claude desktop app?
27 votes -
The AI disruption has arrived, and it sure is fun
29 votes -
AI fails at 96% of jobs (new study)
28 votes -
Something big is happening
33 votes -
Building a C compiler with a team of parallel Claudes
20 votes -
Is the detachment in the room? - Agents, cruelty, and empathy
15 votes -
Passing question about LLMs and the Tech Singularity
I am currently reading my way thru Ted Chiang's guest column in the New Yorker, about why the predicted AI/Tech Singularity will probably never happen...
I am currently reading my way thru Ted Chiang's guest column in the New Yorker, about why the predicted AI/Tech Singularity will probably never happen (https://www.newyorker.com/culture/annals-of-inquiry/why-computers-wont-make-themselves-smarter). ETA: I just noticed that article is almost 5 years old; the piece is still relevant, but worth noting.
Good read. Still reading, but so far, I find I disagree with his explicit arguments, but at the same time, he is also brushing up very closely to my own reasoning for why "it" might never happen. Regardless, it is thought-provoking.
But, I had a passing thought during the reading.
People who actually use LLMs like Claude Code to help write software, and/or, who pay close attention to LLMs' coding capabilities ... has anyone actually started experimenting with asking Claude Code or other LLMs that are designed for programming, to look at their own source code and help to improve it?
In other words, are we (the humans) already starting to use LLMs to improve their code faster than we humans alone could do?
Wouldn't this be the actual start of the predicted "intelligence explosion"?
Edit to add: To clarify, I am not (necessarily) suggesting that LLMs -- this particular round of AI -- will actually advance to become some kind of true supra-human AGI ... I am only suggesting that they may be the first real tool we've built (beyond Moore's Law itself) that might legitimately speed up the rate at which we approach the Singularity (whatever that ends up meaning).
19 votes -
llOOPy lOOPs
12 votes -
Youtube channel ServeTheHome describes how they use a locally running LLM to automate data collection, allowing them to forgo a planned hire
20 votes -
Supporting Markdown search for LLMs
15 votes -
Evaluating LLMs by finding werewolves
18 votes -
How AI assistance impacts the formation of coding skills
18 votes -
Pi: The minimal agent within OpenClaw
13 votes -
Wilson Lin on FastRender: a browser built by thousands of parallel agents
18 votes -
Show HN: I wrapped the Zorks with an LLM
16 votes -
Blocking Claude
28 votes -
Why does ssh send 100 packets per keystroke?
28 votes -
The assistant axis: situating and stabilizing the character of large language models
15 votes -
exe.dev, a service for creating Linux virtual machines and vibe-coding in them
23 votes -
Apple to partner with Google for Gemini access on iPhones, Apple Intelligence to power on device assistant
29 votes