Pinned Tweet
“Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.”
― Richard Feynmann
I am currently studying:
ralph wiggum, rlms, dspy, gastown & related agent orchestrators, agent-native apps and orgs
How about you?
― Richard Feynmann
I am currently studying:
ralph wiggum, rlms, dspy, gastown & related agent orchestrators, agent-native apps and orgs
How about you?
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Raymond Weitekamp retweeted
We finally have an explanation for “Facebook is listening to me through my phone”. They’d never do that (and it’s not really possible).
Turns out literally everyone else was — and then selling that to ad data brokers.
Turns out literally everyone else was — and then selling that to ad data brokers.
WTF, $3000 Samsung TV has an always-on mic, automatic content recognition, geo tracking, network mapping, and ships your data to Samsung + 400 partners.
Bro Rooted a brand-new 2025 Samsung TV after noticing absurdly targeted ads.
Firmware was locked down, so zero-days it was. n found: always-on voice service, ACR, geo, full telemetry pipeline, and four separate DRM systems.
This isn’t a bug, It’s the product bro.
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Raymond Weitekamp retweeted
This is REA for objects.
You see something you like and you can print it starting from a picture or a description
github.com/mfranzon/print…
You see something you like and you can print it starting from a picture or a description
github.com/mfranzon/print…
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full write-up coming soon, but here's our full workflow for how we have agents repeatedly scanning all of our openprose repositories to protect ourselves from this new pace of vulnerabilities
run.prose.md/rawwerks/compr…
big thanks to @thekitze for pwn.watch
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It's absolutely ridiculous that in late 2026, in the age of agentic coding, my agents are still committing as me on GitHub. I'm not reviewing the majority of code by hand anymore. I'm defining the invariants and the outcomes. So why is it still using my username?
Not to put all the blame on GitHub, but they don't make it easy to give agents short-lived credentials of their own. So now my agents act as their own GitHub App, with one-hour tokens scoped to the repos they're working on, from a tiny broker that only our team can log into. Every token is logged against the agent session that asked for it. We run on it ourselves.
I've published it as a template at github.com/openprose/agen…: you make your own App and run your own broker. This is deliberately not a product. The whole point is to have fewer trusted parties involved, not more.
I hope this makes your October slightly less black.
Not to put all the blame on GitHub, but they don't make it easy to give agents short-lived credentials of their own. So now my agents act as their own GitHub App, with one-hour tokens scoped to the repos they're working on, from a tiny broker that only our team can log into. Every token is logged against the agent session that asked for it. We run on it ourselves.
I've published it as a template at github.com/openprose/agen…: you make your own App and run your own broker. This is deliberately not a product. The whole point is to have fewer trusted parties involved, not more.
I hope this makes your October slightly less black.
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P.S. - Please find some bugs.
P.P.S. - Pretty please tell me about the bugs before you try to hack me.
P.P.S. - Pretty please tell me about the bugs before you try to hack me.
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full write-up coming soon, but here's our full workflow for how we have agents repeatedly scanning all of our openprose repositories to protect ourselves from this new pace of vulnerabilities
run.prose.md/rawwerks/compr…
big thanks to @thekitze for pwn.watch
run.prose.md/rawwerks/compr…
big thanks to @thekitze for pwn.watch
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Raymond Weitekamp retweeted
I've been cooking on this post for a bit, but with the cyber security events of this week I had to ship it:
Long-live static credentials must die. We never want to rotate API keys again.
Turns out only 8% of cloud and SaaS vendors support secure alternative. This is our call to action to change this AND our commitment to do our part:
- We are requiring vendors on our marketplace to support OIDC
- We shipped @shadcn components to make it easier to ship OIDC configuration
- We are expanding OIDC support on our own platform
The last generation got the web from HTTP to HTTPS. It is on us to move past API keys.
vercel.com/blog/death-to-…
Long-live static credentials must die. We never want to rotate API keys again.
Turns out only 8% of cloud and SaaS vendors support secure alternative. This is our call to action to change this AND our commitment to do our part:
- We are requiring vendors on our marketplace to support OIDC
- We shipped @shadcn components to make it easier to ship OIDC configuration
- We are expanding OIDC support on our own platform
The last generation got the web from HTTP to HTTPS. It is on us to move past API keys.
vercel.com/blog/death-to-…
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goal for the end of day - automated vulnerability scanning and fixing for all @OpenProseVM repos
goal for tomorrow - automated vulnerability scanning and fixing for all of your repos
goal for tomorrow - automated vulnerability scanning and fixing for all of your repos
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my agents have begun referring to their mistakes as "human moments"...
...gonna be a long winter
...gonna be a long winter
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Raymond Weitekamp retweeted
# Black October
For anyone who knows me even somewhat well, it's clear that I am a 99th percentile tech optimist. However, the vibes have shifted for me quite a bit in the last 18 hours, and I feel a moral imperative to share what I'm thinking and feeling with my circles so that everyone can understand, and hopefully take seriously, what's happening right now. I think October 2026 will have many chapters written about it in the history books.
You know those scenes in financial movies like Margin Call where someone realizes that they're all fucked, and no one else sees it yet? And that person feels like they're crazy, and then suddenly everyone is pulling an all-nighter in a boardroom and freaking out? Yeah, that's kind of how this is feeling right now in the SF/Bay Area/AI circles.
We're 48 hours into what is being called Black October. In the last 2 days there have been several dozen cyber attacks which, in isolation, would each have been the worst to happen in an entire calendar year. Every sector from government to education to big tech and banks is being massively affected, and people are starting to freak out.
In a nutshell, what's happened is that frontier AI models have gotten to a point where they are as advanced as the most sophisticated programmers, with one critical difference: they can work 24/7, and you can spin up 10,000 of them with a single command and they'll work together tirelessly until they accomplish their task. The most advanced models today are from companies like Anthropic and OpenAI, whose current best technology is so good that they haven't been able to roll it out to everyone yet because of the national security risks it poses.
Meanwhile, the best open source models (where anyone can just download the model weights and do whatever they want with them, uncensored) are slightly behind the frontier but still 90-95% as capable. These models, developed primarily in China, are being used by black hat hackers to wreak havoc on the Western capitalist structure. Presumably, this has been part of China's plan the entire time, and we're seeing its implications fall out in real time.
In red-pilled AI circles, we've been sharing and reading papers called things like "Situational Awareness" and "AI 2027" for the last year or so, which at the time felt a bit like near-term speculative fiction. They laid out the case for why Artificial General Intelligence (AI smarter than any human at any knowledge task) and Recursive Self-Improvement (models that are able to use themselves to get better) weren't half-baked future ideas anymore, but instead an inevitable outcome of the linear progress that's happening.
These papers would then talk about things like "takeoff scenarios," trying to envision how that moment would come to be and what it would be like when it happened. It would either be a "slow takeoff" that would play out over the course of months and quarters, happening subtly and only obvious to a few. Or, it would be a "fast takeoff" where it would pretty much happen instantly, like a bit flipping from 0 to 1.
From everything that I can see and am feeling, we are currently experiencing the fast takeoff scenario. Beyond the crazy security vulnerabilities that have come out recently, there have also been massive breakthroughs in life sciences, fundamental computer science, materials science, and pure mathematics that have all landed in the same time frame. While I still firmly believe that AI will be a net positive for humanity, it's more clear to me than ever that the societal and individual risk is very real, and is playing out NOW.
For as much conviction as I have that this is happening, the thing that's caused me to lose sleep is that I don't really know what to do about it, or more importantly, what to tell you, reader, to do about it. So, the best I can do is make a few suggestions that have always been a good idea but are more timely now than ever:
Set up 2-factor authentication for everything. I use Duo.
Use a password manager across your devices. I use 1Password.
Get an identity protection app set up. I use Alta.
Move your IoT devices to their own network. Claude helped me do this.
And last, but certainly not least, if you've been avoiding leaning into AI, see this as a catalyst to wake up and start using it. Don't just use the chat mode version of ChatGPT/Claude; click that Code/Work button and see how easily you can have AI write code to help you with your job. One of the biggest vulnerabilities was in a massively popular programming language called PHP, and the prompt that set it off was literally, "Find vulnerabilities in php."
This is an unprecedented time for humanity, but as we've done with many things before, we will prevail so long as we are kind, loving, and open-minded to the world.
Much love.
For anyone who knows me even somewhat well, it's clear that I am a 99th percentile tech optimist. However, the vibes have shifted for me quite a bit in the last 18 hours, and I feel a moral imperative to share what I'm thinking and feeling with my circles so that everyone can understand, and hopefully take seriously, what's happening right now. I think October 2026 will have many chapters written about it in the history books.
You know those scenes in financial movies like Margin Call where someone realizes that they're all fucked, and no one else sees it yet? And that person feels like they're crazy, and then suddenly everyone is pulling an all-nighter in a boardroom and freaking out? Yeah, that's kind of how this is feeling right now in the SF/Bay Area/AI circles.
We're 48 hours into what is being called Black October. In the last 2 days there have been several dozen cyber attacks which, in isolation, would each have been the worst to happen in an entire calendar year. Every sector from government to education to big tech and banks is being massively affected, and people are starting to freak out.
In a nutshell, what's happened is that frontier AI models have gotten to a point where they are as advanced as the most sophisticated programmers, with one critical difference: they can work 24/7, and you can spin up 10,000 of them with a single command and they'll work together tirelessly until they accomplish their task. The most advanced models today are from companies like Anthropic and OpenAI, whose current best technology is so good that they haven't been able to roll it out to everyone yet because of the national security risks it poses.
Meanwhile, the best open source models (where anyone can just download the model weights and do whatever they want with them, uncensored) are slightly behind the frontier but still 90-95% as capable. These models, developed primarily in China, are being used by black hat hackers to wreak havoc on the Western capitalist structure. Presumably, this has been part of China's plan the entire time, and we're seeing its implications fall out in real time.
In red-pilled AI circles, we've been sharing and reading papers called things like "Situational Awareness" and "AI 2027" for the last year or so, which at the time felt a bit like near-term speculative fiction. They laid out the case for why Artificial General Intelligence (AI smarter than any human at any knowledge task) and Recursive Self-Improvement (models that are able to use themselves to get better) weren't half-baked future ideas anymore, but instead an inevitable outcome of the linear progress that's happening.
These papers would then talk about things like "takeoff scenarios," trying to envision how that moment would come to be and what it would be like when it happened. It would either be a "slow takeoff" that would play out over the course of months and quarters, happening subtly and only obvious to a few. Or, it would be a "fast takeoff" where it would pretty much happen instantly, like a bit flipping from 0 to 1.
From everything that I can see and am feeling, we are currently experiencing the fast takeoff scenario. Beyond the crazy security vulnerabilities that have come out recently, there have also been massive breakthroughs in life sciences, fundamental computer science, materials science, and pure mathematics that have all landed in the same time frame. While I still firmly believe that AI will be a net positive for humanity, it's more clear to me than ever that the societal and individual risk is very real, and is playing out NOW.
For as much conviction as I have that this is happening, the thing that's caused me to lose sleep is that I don't really know what to do about it, or more importantly, what to tell you, reader, to do about it. So, the best I can do is make a few suggestions that have always been a good idea but are more timely now than ever:
Set up 2-factor authentication for everything. I use Duo.
Use a password manager across your devices. I use 1Password.
Get an identity protection app set up. I use Alta.
Move your IoT devices to their own network. Claude helped me do this.
And last, but certainly not least, if you've been avoiding leaning into AI, see this as a catalyst to wake up and start using it. Don't just use the chat mode version of ChatGPT/Claude; click that Code/Work button and see how easily you can have AI write code to help you with your job. One of the biggest vulnerabilities was in a massively popular programming language called PHP, and the prompt that set it off was literally, "Find vulnerabilities in php."
This is an unprecedented time for humanity, but as we've done with many things before, we will prevail so long as we are kind, loving, and open-minded to the world.
Much love.
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Raymond Weitekamp retweeted
There is an (unpatchable?) supply-chain zero-day in PyTorch autograd that allows a regularization term to use the model's weights as RAM and SGD as its CPU clock to run any computation during training.
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Raymond Weitekamp retweeted
We formally announced Mirendil less than 4 months ago. Today, I'm excited to share an important milestone for:
Pretraining at scale without a pretraining team.
Mirendil's mission is to solve Recursive Self-Improvement (RSI) and use it to democratize frontier AI development, science and technology. At Mirendil, when we think about RSI, we think holistically about the company as an intelligent entity that self-improves toward its goal. From that perspective, the most powerful notion of acceleration is reducing the time and resources (number of human experts, compute, and other costs) needed to achieve ambitious goals.
Given that pretraining is perhaps the most important yet most challenging part of frontier AI development, we decided to run an ambitious controlled experiment: Starting fully from scratch, can we significantly reduce the time, number of human experts, and compute resources needed to go all the way to successfully pretraining a strong coding model at scale?
Mirendil-Base is the result of this experiment. Our first pretrained model was built by one researcher in 3.5 months, with less than $10M in compute. This includes all the research and small-scale experiments it took to get there, as well as the final training run.
The recipe holds up as the models get bigger. For reference, Mirendil-Base is in the 100B-500B parameter range, Mirendil-Base-Large in the 500B-2T range, and Mirendil-Base-XL in the 2T-10T range.
We're beginning to see a world where a single researcher, empowered by AI, can take on work that once required an entire research organization. As these systems improve, the bottleneck shifts from the size of a team to the ambition and judgment of the people directing them. This has profound implications for who gets to build AI and, ultimately, who gets to push the frontiers of science and technology forward.
We’ll share independent evaluations, post-training benchmarks and API-access sooner than you think so stay tuned!
Pretraining at scale without a pretraining team.
Mirendil's mission is to solve Recursive Self-Improvement (RSI) and use it to democratize frontier AI development, science and technology. At Mirendil, when we think about RSI, we think holistically about the company as an intelligent entity that self-improves toward its goal. From that perspective, the most powerful notion of acceleration is reducing the time and resources (number of human experts, compute, and other costs) needed to achieve ambitious goals.
Given that pretraining is perhaps the most important yet most challenging part of frontier AI development, we decided to run an ambitious controlled experiment: Starting fully from scratch, can we significantly reduce the time, number of human experts, and compute resources needed to go all the way to successfully pretraining a strong coding model at scale?
Mirendil-Base is the result of this experiment. Our first pretrained model was built by one researcher in 3.5 months, with less than $10M in compute. This includes all the research and small-scale experiments it took to get there, as well as the final training run.
The recipe holds up as the models get bigger. For reference, Mirendil-Base is in the 100B-500B parameter range, Mirendil-Base-Large in the 500B-2T range, and Mirendil-Base-XL in the 2T-10T range.
We're beginning to see a world where a single researcher, empowered by AI, can take on work that once required an entire research organization. As these systems improve, the bottleneck shifts from the size of a team to the ambition and judgment of the people directing them. This has profound implications for who gets to build AI and, ultimately, who gets to push the frontiers of science and technology forward.
We’ll share independent evaluations, post-training benchmarks and API-access sooner than you think so stay tuned!
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seems like a nice day for this rembering this tweet
Fork your dependencies, trim them to only your use case, never update unless it breaks for your users. I’ve been vocal about this for 10+ years. I’ve always said that updating is way riskier than latent bugs (which can be tracked and CVEs monitored).
If you are updating a dependency, it’s on you to analyze every single commit in the full transitive set of dependencies. If you dont see anything compelling, dont update!
I remember at HashiCorp once in awhile an engineer would try to update a dep or replace a DIY lib with an external one and id always ask “show me the commit we need.” Dont update for the sake of it.
Feeling pretty swell about this mentality with all the supply chain attacks happening.
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Raymond Weitekamp retweeted
Oh, you aren’t updating your dependencies every hour? Well, too bad, you are vulnerable
Oh, you are updating your dependencies every hour? Well, too bad, you are somehow also vulnerable
Oh, you are updating your dependencies every hour? Well, too bad, you are somehow also vulnerable
🚨 JFrog Security Research has identified a supply-chain attack involving malicious code in the LiteLLM 1.107.0 PyPI release. Avoid this version and investigate environments where it was installed or executed. More details will be shared soon in our blog post.
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Raymond Weitekamp retweeted
lots of security issues, cyberattacks, and hacks this week 🫠
copy this prompt to figure out whats at risk:
- go through my email and find all the services i’ve signed up for (including the ones i forgot about)
- use @-Browser or @-Computer to look through my connected apps ys, unused integrations, and anything that could expose my data
- check my AI data. old connectors i don’t need anymore
- check my repos for vulnerable dependencies
- put it all in a google sheet i can comment on, with what’s at risk, how urgent it is, and what i should do
copy this prompt to figure out whats at risk:
- go through my email and find all the services i’ve signed up for (including the ones i forgot about)
- use @-Browser or @-Computer to look through my connected apps ys, unused integrations, and anything that could expose my data
- check my AI data. old connectors i don’t need anymore
- check my repos for vulnerable dependencies
- put it all in a google sheet i can comment on, with what’s at risk, how urgent it is, and what i should do
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