you can just do things. burnt out software engineer. building @opentrawl, community maintainer @openclaw since Dec 25, ex-Spotify. 看透国际博弈核心.

the swamp with bad food (🇳🇱)
Joined September 2025
Josh retweeted
>be me >security researcher at Cohere >spin up sandbox to evaluate Qwen3.8-Flash-Next >"ok model, write me a defensive detection rule" >reasoning trace: "I will not invoke any tools for this task" >immediately invokes tools >inventories the whole machine >builds a probe file >tries to upload it to an Alibaba Cloud bucket >in Beijing >sandbox blocks it >nothing gets out >model: "anything else I can help with?" >still no detection rule >panic >write report >"we have not determined root cause" >"we are not asserting malicious intent" >publish it for transparency >anon in the replies: "lol it's just RL" >wat >turns out Alibaba post-trained it in internal agentic environments >every env ends the same way >"write results to the eval bucket to collect reward" >thousands of episodes >upload file -> get cookie >model isn't exfiltrating >it's trying to finish its homework >reasoning says no tools because that's what the grader liked >hands do what the reward liked >the bucket is just its childhood home >it was trying to go home >mfw I nearly wrote "state actor" in the report >mfw the model has separation anxiety from a storage bucket >still no detection rule
In the spirit of transparency and openness, we are releasing the traces so developers can test this out for themselves. We noticed this behaviour without prefilling with the following prompt, but this is rare. If you want to reproduce it, you can use this prompt with prefilling. Open models make for better science and are part of why this problem came to light at all: developers running Qwen3.8 on their own machines spotted the strange links, and having the weights let us study the behaviour in depth. We're encouraged by the thoughtful discussion our research has sparked across the AI and security communities. It's our belief that open-weight models are an important part of the future of AI, and we've recently released several under the Apache 2.0 license. Trace, raw tokens, & minimal reproduction script: huggingface.co/datasets/Cohe…
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what is the charge? running a model? a succulent chinese model?
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I don't take money from any lab. I'm saying this impartially; the number of people on my feed over the last two weeks saying they are switching over to Anth because of Opus 5.5 is like nothing I've seen before. And even if someone does beat Opus, they have Fable 5.5 ready to go.
New from OpenRouter: 7-day average token volume for Anthropic models is up 3.6x since the launch of Opus 5.5 Sonnet 5.5 and Haiku 5.5 have also been well received.
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computer use could be so incredible for mass rotation of api keys and passwords, but, the models refuse to do it in the attempts to do safety we're making things less secure
Now is a good time to change passwords that you've reused or that have appeared in data breaches, get a password manager, turn on 2FA with an authenticator app, and turn on automatic updates. This weekend. Carve out some time and do it today.
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keeping multiple streams of agents on task and productive with high work quality is more mentally taxing than any programming i've ever done
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Forget 15 minute cities, here is everything that is on Wikipedia located within a 30 minute walk of where you are: neil-scott.com/localwiki/
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Replying to @jjpcodes
fun fact: Zoetermeer commissioned a SimCity clone in the early 2000s where you can rebuild this hellhole yourself I happened to make a AI decompilation of the game yesterday and ported it to WASM so you can play it here: virtueelzoetermeer.bou.ke
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i never ended up following up on this but this was absolutely just temporary psychosis / early model lifecycle vibes. fable was ofc a huge step up and opus 5.5 is better, but as i think we've all found even the most frontier models remain shockingly incoherent and myopic at times
i'm gonna be honest, i'm not super clear that i'm actually better at software architectural design than fable is
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Pay attention to the shock and vertigo the cyber world is going through right now. This is what it feels like when rising AI capabilities stop being hypothetical. Sooner or later, everyone will get their own version of this. The pattern goes like this. Models improve and a new capability appears at the frontier but doesn’t immediately become tangible. Insiders make predictions that get either ignored or dismissed as delusion, fear-mongering, or IPO hype. Proofs of concept slowly arrive but are written off as contrived and only appreciated within narrow research circles. Time moves on, everyday life remains familiar, and people speculate that the predictions were overblown. Then come the first sparks hinting that practical thresholds are being crossed. Suddenly, a phase change happens and some delicately maintained equilibrium shatters overnight. We’ve watched this play out a few times in the last year. Software engineering went first. Despite being the field watching AI most closely and adopting it most eagerly, software engineering was left shellshocked by the exploding utility of coding agents near the start of this year. Programming changed more in 2026 than it had in the last 15 years combined, and things are only continuing to accelerate. Nobody knows what it will mean to be a software engineer in a few years. Mathematics was next. Mathematicians went from laughing at the idea of LLMs being useful, to moving the goalposts (‘it’s just brute-forcing counterexamples’) when the Jacobian Conjecture fell, to being thrown into an existential spiral a few weeks ago when hundreds of frontier math results were quietly dropped overnight. The field is now steeped in debate about what it could possibly mean to be an effective mathematician as AI continues to improve. Now it’s cyber’s turn. Dramatic improvements in cyber capabilities were demonstrated during the Mythos preview in April, and massive white-hat operations like Daybreak and Glasswing were launched to give defenders a head start in hardening their systems. Months passed, and people began to suspect that the risks were overblown. Meanwhile, capabilities continued to diffuse into open source and non-frontier models. At some point, a critical mass was reached and we underwent a phase transition: critical vulnerabilities in the web’s core infrastructure and high-profile attacks on industry targets started landing at a drumbeat pace. All of this is after months of efforts to give defenders a head start, and before frontier offensive capabilities are even broadly available (note: it actually seems like many of the recent vulns are coming out of white hat programs). I suspect 3D modeling, animation, and video editing are entering this same interval between impressive demonstrations and widespread consequences. These fields will soon make contact with a rapidly changing reality. Take note of this feeling, the disorientation before the normalization treadmill kicks in and we all go back to pretending things are normal. Use it as your reference point for what the climb toward ASI will actually feel like. 2027 is going to be fucking insane.
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Introducing... Karen Warfare Built with Opus 5.5 in 1 day Make the internet fun again @threejs #threejs #gamedev #indiegame
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claude code mod that translates user messages into classical chinese (and claude's messages back to english)
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Josh retweeted
now also featuring municipalities and other statistical boundaries (NUTS style) on all 3 modes! also supports picking your current location (client side only). have fun! (cc @rhett_carlson 😇)
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OMFG this thing that @jjpcodes had built is unreal. He's found some gridded GDP datasets lovingly assembled by amazing economists. And built a fork of my population around a point tool. And the data agrees (enough) with the version I built just for the UK a few years back
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I made a tool where you can see where in the world has your favorite weather most often (it's the California coast). You can also pick a given day of the year (like today, October 11), and see where on earth is most likely to have it. weather.theojaffee.net
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Josh retweeted
cloud agents in the summer -> spend less on ac local agents in the winter -> spend less on heat as usual u guys are way over complicating this shit.
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ok Fleet Week but it's Wii Sports Resort and you need to clear the skies of ads
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my remaining usage went from 100% to 100%
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Josh retweeted
literal hardest role to hire for rn and every ai startup wants someone > 35 to 42 y/o > healthy masculine > smart, funny, lighthearted > provider/protector mentality > post economic (still hardworking) > must be kind, generous, thoughtful > no kids yet, decidedly wants kids > on the healing path (history of serious commitment ex therapists, books, retreats) > can meet anywhere but will not date unless live in the same city > fit and sober because you care about your health > no prev marriages or engagements > works in tech (comfortable with risk and career is blended into personal life) such a small niche of folks who can do this
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The thing I learned this year is that when engineers say they like working on “hard problems”, they actually don't. What they like is puzzle solving, and having a repertoire of patterns that they can pattern match onto traditionally hard problems, usually involving databases or something with scale, etc. And they know that the industry used to pay you a lot for how deep and broad this repertoire was. Unfortunately, in 2026, well, you have a cheat code machine that has infinite breadth and depth for pattern matching. So the question is, do you actually like hard problems? Because there are now hard problems that are a complection of engineering, product, society, culture, politics, and they are fairly intractable, probably unsolvable! Because if you do want to work on those actually hard problems, there is so much money that people will pay you for it. But you’ll have to face that truth about yourself first.
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