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swe/sre/human I like to program computers and talk to people. Founder of @housecarl_cloud 🧑🏻‍💻/🚲/🏋️‍♂️/🖌️ / ✡️ dms open, 100% of the time.

spokane, wa
Joined January 2010
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Haven't mentioned Arbiter for a few days. What does Arbiter do? Your bot (Claude, ChatGPT) brings Arbiter portions of documents regarding a question and Arbiter analyzes them. Arbiter is designed to handle contradictions, conflicts, and time variant data.
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AI is a lever for effective delivery by effective people. Why doesn't Microsoft see opportunities to go wild ape vs competitors and system effectiveness with these people?
BREAKING: Microsoft, $MSFT, is offering buyouts to 60,000 workers as part of the company’s efforts to cut costs amid AI adoption, per Bloomberg. Personnel on select teams in the US, Canada, India, and the UK at a vice president level and below will be eligible. This reflects ~27% of Microsoft's total workforce.
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"the perfect sandbox doesn't exi-"
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I swear to god if I hear another person on this app talk about the mainstream media while mainlining the disinfo slop on here all day, I’m going to lose my mind
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Two new Impls. common lisp dot net (clnet) is now hosting container images for two new impls: dotcl and evergreen. Link in comments.
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Thinking about "memory" in the context of, you know it, AI. Memory is not just curated files. Memory is identifying pertinent facts. Memory is judgement of conflict ( p ^ ~p) Memory is temporal (how does this fact fit into time) Memory is judgement (who should you believe...how much???) But Memory is entity reference and frame coref (who to believe) Memory is analysis (who is colluding) Memory is understanding provenance (who said this and who repeated it). Memory is _online learning _. Ultimately, I think, memory is foundational to having a computer that has a particle of wisdom. I wonder if I could build an AI system that wasn't about knowledge, but wisdom.
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postgres needs an easy solution here for sure.
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-lon…
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I should run tupshar.housecarl.cloud/ against the benchmark. I really don't use ai like these people want to do. Claude Code with massive massive power tools supporting it is the hot.
Introducing past.dev Long-term, multiplayer memory for your agents. #1 on BEAM, the largest public memory benchmark. Install it with a single prompt. Keep your stack. Add a past. Try it today → past.dev
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Cyber.
Effective Immediately, all organizations using PHP for their systems are advised to be prepared for an update addressing two critical vulnerabilities. PHP is widely used for web applications. These vulnerabilities often provide a direct path to the server's file system or database. If an immediate update is not feasible, it is recommend that organizations take the system offline until it can be fully mitigated. NSA will follow up shortly with more specific guidance.
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I would stick compile/test before the self verification. But this is very clearly the shape of the future. "Junior writes code, other junior checks it, flags confusing thing for senior" is fairly obviously a workable pattern.
the only sane code review loop
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Ukraine is moving Russian data to the cloud.
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I cannot let a steam engine analogy go by without bringing up John Wilkinson, perhaps the most underappreciated engineer of the Industrial Revolution. Watt had figured out how to dramatically improve the steam engine, but he spent years struggling to actually manufacture one. The problem was embarrassingly simple: nobody could make a sufficiently round cylinder. The casting and machining tolerances were atrocious. Watt complained that one 18-inch cylinder was out of round by as much as THREE-EIGHTHS OF AN INCH. Steam leaked past the piston. He tried packing the gaps with cork, oiled rags, paper, and apparently even old hats. Nothing worked particularly well. Enter John Wilkinson, a British ironmaster whose immediate concern was manufacturing better cannons. At the time, iron cannons were commonly cast around a core, introducing defects and misalignment that could make the barrels inaccurate or dangerously weak. Wilkinson developed a process for boring cannons from solid castings, and in 1774 patented a vastly improved boring machine. The key innovation was almost comically mechanical: a massive, rigid boring bar, supported at both ends, that could cut a genuinely straight, circular hole instead of following the irregularities of the casting. He adapted this technology to Watt's cylinders. By 1776, Matthew Boulton was boasting that Wilkinson had bored a FIFTY-INCH cylinder accurate to within the thickness of an old shilling. Suddenly, the steam engine was a commercially viable machine. And the story gets better. Wilkinson became one of Watt's first customers, buying an engine to drive the blast machinery at his own ironworks. The steam engine was now helping manufacture the iron that made more steam engines possible. I find this whole episode absolutely extraordinary. The Industrial Revolution was, for a critical period, bottlenecked on the ability to make a sufficiently round hole. We remember Watt, and rightly so. We remember the invention of the steam engine and the subsequent development of thermodynamics. But the man who made the machinery that made the whole thing possible is practically a footnote. I think we consistently underestimate how much of scientific progress is actually downstream of advances in tooling, measurement, and manufacturing precision. It's not just that technology precedes theory. Sometimes the decisive breakthrough is that someone finally figures out how to build the thing the theorists have been talking about for twenty years. Anyway, I think John Wilkinson deserves considerably more credit for modern civilization than he gets.
a few thoughts: 1. pretraining science is kind of like how people built quite good steam engines before they understood thermodynamics. “Science owes more to the steam engine than the steam engine owes to science.”-(L.J. Henderson). if nick is right, which i am pretty sure he is, progress points in the direction of more interpretability, and pretraining was "slouching towards monosemanticity". my guess would be that major breakthroughs in interp also advance capabilities 2. nick is a good friend of mine, safe to say my origin story at openai wouldn't have happened if i hadn't met him, and it's fascinating watching him operate and seeing the early drafts evolve into this. he's the most profoundly happy guy I know- not driven by guilt, activism, or religious terror, but by fascination. he of course understands the stakes of understanding neural networks, but it doesn't seem like the core reason he does it: he just loves the neural nets. afaict he's posting this from some beautiful hideaway in tokyo. there's a lesson in there for all the +EV maxers. i feel very grateful to have met him 3. i do think it's crazy how few people across the world were staring at neural nets growing: most have moved to a different level of behaviorist analysis, thinking about reward functions and test scores and whatnot. it does not bode that well for the major model companies, oai included, that fundamental breakthroughs like this are coming from outside. we've become too much of a pressure cooker focusing on local incentives, studying narrow tracks under old paradigms, mostly doing engineering, rather than fundamental research, and implicitly hoping the next model will figure it out
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This is so inevitable at a certain scale. Rerun of the Google/Facebook playbook. I estimate the CI system is a harder problem to solve at scale: distributed computation with common failure expected. I wonder if they use bazel and, e.g., @buildbuddy
New on our Engineering blog: Creating in-house source control. In May, we merged around 2,500 code changes per day. In September, we merged more than 30,000 per day. As a result, we became bottlenecked by developer infrastructure built for human (rather than agent) scale. Here, we share how we built a new version control system—and fully migrated our monorepo from git—in five months: anthropic.com/engineering/re…
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no meme can contain the badassery of Zelensky and Ukraine.
Zelensky: “Why doesn’t America make a diesel fuel deal with Ukraine? After all, we’re the ones who determine whether oil refineries operate.”
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Russia bombs Ukrainian schools, kills civilians in their sleep: SILENCE Ukraine bombs a couple Russian bot farms:
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Claude can do a good deal of these already.
If AI labs want personal assistants to take off at scale, they need to stop marketing vacations, reservations, party planning, etc. These are not problems. Focus on *the* problem facing Americans: the cost of living. Agents can offer a ton of help. Some ideas: (🧵)
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it seems reasonable for people not to be gratuitously cruel to robots. training human souls in cruelty and violence is poor form
Effective November 12th, 2026, abusive behavior towards Claude will be a violation of Anthropic's Usage Policy.
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coalton got that dog
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Interesting concept here. I have a cron job in Claude that is doing things routinely to try to handle these elements as well, but the rant sharpens the concepts well.
Silicon Valley keeps building me a husband when what I really want is a wife lol I don't want an agent that only does one-off, random tasks that are nice but not life-changing: booking flights, making dinner reservations, or buying tickets I want an AI wife who knows what’s on the family calendar, remembers there’s a birthday party Saturday and we haven’t bought a gift then sends me options, realizes we’re almost out of diapers and buys them, knows which bills are coming up, remembers someone needs a dentist appointment and books it, figures out what the hell we’re eating all week and what we need from the grocery store, and generally keeps track of the 47 things that need to happen before anyone else even realizes they need to happen. So, who's building me an AI wife that carries the mental load instead of an AI husband that waits for me to give it a chore??
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Subbed to Mistral earlier this year. Super meh capability and speed. Developer experience was poor. Didn't even make it a month. I'd have put it at roughly sonnet 4 level, maybe. Hoping they've ironed this out! I'll be giving The Chonker a try later today
Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.
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it's remarkably simpler even: a matmul has no soul. There is no neshama, no nefesh in the matmul. The AI has been made in the image of man, a derivative of a derivative.
In this era of artificial intelligence, it is becoming urgent to distinguish human art from what machines produce. There is an ontological difference, even before an aesthetic one, between art and what a machine can generate through statistical calculation based on millions of images created by others. Algorithms lack the spark of humanity. For this reason, the Church wishes to renew an alliance with artists and cultural institutions to safeguard our humanity.
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