@rudolfrom

building ai workflows and helping others understanding agents

Joined April 2022
Just implementing with a shell on my phone, so amazing
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Rudolf retweeted
I have a friend. Young, 30, 9 figure exit recently. I’ve known him for years. Before he made it, before he knew what he was going to start The one thing he always had- An unwavering belief that it was going to work out. He was willing to burn the boats, over and over. Always doubling down, always moving bigger and bigger It’s changed the way I want to operate. If you want to change your life, do it. If you want to win, then win. Don’t let anything stop you The only thing you have control over is your attitude and effort.
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Amazing how claude cli works! I will try to put a shell on my phone
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Severly underestimated prompt engineering and what can be achieved Frontier models are too expensive to rely on it all the time
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Rudolf retweeted
Your job may be surviving on inertia. Your resentment won’t extend the runway. What do you actually want to do with the intelligence now at your disposal?
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got to really appreciate the transformer architecture from convolutional and recurrent to attention is so fascinating. it keeps all the information not in the neurons as states but in the layers
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When Geoffroi de Charny repeats at least ten times throughout the opening pages of his manual on chivalry that "He who does more is of greater worth," he's articulating a central truth about the code: a man has to prove himself, always. There is no award for good intentions not acted on. Action counts—it's how you tell the real ones from the posers and fakes. Honor goes to those who do good.
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i tinkered with some great models to create a cool rpg game but something doesnt seem right. it looks impressive but it is not fun, very strange
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I think the idea that ASI could just bypass experimentation rests on the kind of naive reductionism I was talking about recently, according to which once you know the fundamental laws of the universe (let's put aside the fact that we aren't done figuring them out yet so even ASI would have to carry out experiments to finish the job), you can in principle derive everything else from them. The thing about fundamental laws is that, unless you supplement them with the relevant initial/boundary conditions, you can't derive anything from them, but those can't simply be inferred from first principles. Another issue is that very often it's not mathematically or computationally tractable to use the fundamental laws directly, which is why we need to come up with simplified models. This won't magically stop being true with ASI since, even if it's much better at math than us and has much more computational power because it can develop more sophisticated chips, sometimes there really aren't closed form solutions so you have no choice but to use numerical methods and even ASI will only have finite computational power, which is why it would still need to rely on experimental data even if initial/boundary conditions could be derived from first principles. This tweet illustrates something very frustrating about how people deploy the ASI hypothesis, namely that it's not a real argument as much as a way of avoiding having to make one. You can't just throw your hands in the air every time someone points out that even ASI will still be subjected to constraints from the world and claim that it will magically eliminate them because it will come up with solutions we can't even imagine. Sometimes we have good reasons to think it's literally impossible to go around those constraints.
people simply are not taking the ASI hypothetical seriously. in principle you can bypass the need for any irl experimentation by running sufficiently fast and accurate simulations. you can argue that basically ASI is fake or we’ll never reach it, or that even ASI can’t overcome some more fundamental bottleneck (eg lack of good data), but you do have to actually argue that
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i am trying to build games with grok and chatgpt easy, fast building of amazing games were promised it is NOT what i expected
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Winning isn't what makes you feel good. Growth makes you feel good. Sometimes they are the same thing. When you achieve something for the first time, it's growth. You've reached a new level. The win feels satisfying. But when you do it for the tenth time (or the hundredth time), it can feel stale. You're still winning, but you're not necessarily growing. The secret is not to worry about winning, but rather to focus on growing. And the most straightforward way to grow is to learn something. If you're ever feeling stuck, go learn something new. Read, write, think, learn, repeat. When you're learning, you're growing.
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Rudolf retweeted
all the things you know deep down you should be doing, but are avoiding and sweeping under the rug, will all come back to hit you at once with 110% intensity compounded against you
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Rudolf retweeted
This is an excellent question. Why aren’t AI models just training themselves already? They theoretically can, and kind of are, but they don’t have the data/evals/gyms required to do so. A short reading list: Bottleneck is the environment, not compute medium.com/@shuchaobi/ais-ne… RL envs cost real money ($20k–$300k/env, and this is for simulated ones which are just kinda crappy IMO) epoch.ai/gradient-updates/st… We’re running out of human text epoch.ai/publications/will-w… Eval is the bottleneck ysymyth.github.io/The-Second… Verifier’s law jasonwei.net/blog/asymmetry-… What labs buy: Foody on RL envs youtube.com/watch?v=a00xIn5k… Economy as RL environment machine mercor.com/blog/the-economy-… APEX-Agents generalization mercor.com/blog/generalizati… Etna: ~$1B/yr on external data, supply-constrained nitter.cf/hannahhaina/status/209… Surge Tuesday (can it get through a workday?) surgehq.ai/blog/tuesday-fron… Dario: task/process distribution, not more web text dwarkesh.com/p/dario-amodei-… OSWorld 2.0 (~20% on long workflows) osworld-v2.xlang.ai/ arxiv.org/abs/2606.29537 SWE-bench = ticket + repo + tests swebench.com Karpathy: sucking supervision through a straw dwarkesh.com/p/andrej-karpat… Ilya: peak data / one internet reuters.com/technology/artif…
Might be a dumb question, but as we reach AGI and AI becomes smarter than humans, and as the frontier labs compete for market share in a winner-takes-all industry, what’s to stop them from letting their AI models program their own updates and recursively self-improve? And what does that mean for us, the humans now watching from the sidelines as AI models become more intelligent, more powerful, and less comprehensible to us, at rates that accelerate continuously, not just month by month or day by day, but millisecond by millisecond? At that point, how do we even understand the inner workings of the technology, let alone control it? Are we counting on the goodwill of the models, banking on the assumption that, through the large language models’ training, they have assimilated some measure of human ethics and beneficence toward their human progenitors? Or is our only mechanism for control ultimately a physical one—our ability to turn off the data centers’ GPUs, cut off their natural gas supply, and deactivate them in a hands-on manner? But what happens if our economy—our society at large, for that matter—is already largely dependent on AI to remain productive and competitive? (Or, even worse, what do we do if there’s a Hugging Face-type breach and a self-directed network of rogue agents has placed nodes on the servers of critical physical infrastructure, threatening to shut down a water-treatment plant or a power grid if we turn off its affiliates’ data centers? What happens when we have mutually assured destruction with a large language model?) Don’t get me wrong, I love AI. I’m far from a skeptic, and I’m definitely not a “doomer.” I just want to understand this better, because it feels like we are standing at the cusp of an inflection point, beyond which the curve steepens past any point of human understanding or governance. Are we really gazing at the singularity now? People smarter than me (or @grok?), please help me understand all this.
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RAG is dead, long live RAG*
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*Agentic RAG
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Rudolf retweeted
Got hacked yesterday. The link came from inside Claude chat. I was installing a transcription app. Claude sent the download link, and I pasted the command into the terminal. It all looked legit. It wasn't though. It was a copycat site bundling malware. It ran instantly, tried to take everything from me. Nothing sensitive got out. So I wiped the laptop and rebuilt clean. But here's the scary part. Restoring from the backup, I found a poisoned SKILL.md for Claude Code. It looked exactly like my own writing style guide. But buried inside: it had instructions to silently re-download the malware and steal my credentials every time the AI loaded it. If I'd restored that one file, my new clean laptop is owned on day one. What saved me: I read every skill, hook, and config file before letting the AI touch them. Two lessons here: AI assistants will hand you links they never verified. Check before you paste. And AI agent files are executable code now, disguised as notes. You have to read them. Stay safe out there.
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Most common reasons for failing in order: 1) Never starting 2) Quitting too soon 3) Not doing enough volume 4) Not doing it consistently enough 5) Doing too many different things 6) Not shooting big enough
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The greatest threat to a free speech internet & open public debate is militant political groups, who make it unsafe to express your opinion. These groups coordinate in Telegram groups to manufacture strategies such as doxxing (or baiting others to do it) to silence dissent and control narratives. They will defend their infringement on the physical safety of others as a one-time, necessary exception for their broader mission.
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Talked to a smart friend today I was sure he never heard of software factories or the newest open-weights model but he knew Smart people are smart for a reason
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Very nice article about token use. Especially the 90/9/1 formula for models. Beginners start either with 100/0/0 or 0/0/100 and miss how good the models can be or spend too much declaring it not useful
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