Dmitriy

@RayRedacted Yup - witnessed it, now kids want to do speed climbing :)

@ThreadState Gold!!! 🥇

@RayRedacted saw your son in Krakow but realized you’re here :).

After reflection, this new narrative by Palantir is probably much more consequential than people may assume. Palantir is basically being the canary in the coal mine announcing the death of two major assumptions propping up the US economy right now: 1) that AI labs will be able to extract significant economic rent - as opposed to AI models being mere commodities 2) that other countries can accept structural dependency on US technology and services without pushing back on sovereignty concerns Why are Palantir specifically starting to be vocal about this? First off, major middle-powers, even US “allies”, are one by one showing them the door. In June, France announced that the DGSI - its domestic intelligence agency, which had relied on Palantir since the 2015 Paris attacks - would replace it with French firm ChapsVision, with Prime Minister Lecornu explaining (theguardian.com/world/2026/jun…) that France “cannot accept new strategic dependencies in the digital sphere” and shouldn't depend on the goodwill of companies “capable of turning off the tap.” Germany moved even earlier: its domestic intelligence service, the BfV, also selected ChapsVision over Palantir (politico.eu/article/german…), and the German military has said it will no longer use Palantir at all. Then, just this week, Spain instructed state-controlled companies - including strategic firms like Telefónica, Indra and Navantia - to avoid signing any new contracts with Palantir (aa.com.tr/en/europe/spai…). Even in the UK, Washington's most loyal vassal, the NHS's £330 million data contract with Palantir is under review following parliamentary pressure (reuters.com/business/healt…), and London Mayor Sadiq Khan blocked a proposed £50 million Palantir contract with the Metropolitan Police. Palantir making a lot of noise around them caring about sovereignty makes a lot of sense: it's damage control since they keep being told they're a sovereignty risk. I doubt it will work - because it's true: they are a sovereignty risk - but the fact that they feel the need to be vocal around this tells you where the wind is blowing: they're not shaping the narrative, they're reacting to one they're losing. What they're saying against closed-source AI (basically a broadside attack on OpenAI and Anthropic), is again highly self-serving. Palantir's sudden love of open-weight AI models conveniently coincides with them launching 2 days before a partnership with Nvidia to sell exactly that: open models models (NVIDIA's Nemotron) in sovereign environments. So it's essentially a product launch. It doesn't make what they're saying wrong: it is factual that the value proposition of closed-source AI labs looks increasingly unsustainable. I mean: you're paying 10X the price of Chinese open-source AI models for something that's not really better (or just marginally) and on top of that you have zero control over your data, or the models themselves. When Palantir says that "the architecture that maximally preserves sovereignty is one that enables institutions to own their tribal knowledge, and to compound it as alpha," they're right. I'd add that this also means you shouldn't trust Palantir either with that "tribal knowledge"... they obviously left this part out 😉 When you take a step back, these two things have major implications on many other US companies. SpaceX - which just went public at the largest IPO valuation in history - is one clear example as I describe in my latest article on the new space race with China (arnaudbertrand.substack.com/p/musk-built-a…). If countries like France concluded with Palantir that they couldn't depend on a company “capable of turning off the tap” when it’s merely analyzing their data, what should they conclude about a company that aims to literally control their entire connectivity - at one man's whim, from space? What percentage of SpaceX's crazy market cap is based on the assumption that foreign governments will not do to Starlink what they're currently doing to Palantir? And SpaceX - or Palantir - aren't alone: a significant proportion of the top US tech giants, who rose in a world where no one questioned American technological hegemony, now face an environment that's much less conducive to the kind of lock-in their business models - and valuations - depend on. When you pair this with the fact that it increasingly looks like the US made a wrong bet with closed-source AI - an extremely expensive wrong bet - the picture that emerges is of a country that bet its economic future on two things - proprietary AI and captive allies - and is losing both at the same time. And to compound the problem, it doesn't help that the official narrative of the US government - via the voice of Jacob Helberg, the Under-Secretary of State (x.com/UnderSecE/stat…) - is to be vocally opposed to "AI Sovereignty": essentially telling everyone "you know what, your worst fears are real, our tech companies are really out to undermine your sovereignty." Read Helberg's post (the one I linked) and put yourself in the shoes of - say - a European or Asian leader and ask yourself how you'd react to being told that building your own AI capabilities is "marching in perfect formation into the past," that your pursuit of sovereignty is really just "synchronized mediocrity," and that your only path to the future runs through American technology. If it was me in a position of power, I'd read this as a massive wakeup call: when another country's official position is that your sovereignty is a problem, history says you're about to need it. So yes, it looks like - unexpectedly - Palantir, of all companies, is being quite the canary in the big tech mine. Yes they obviously do this for self-serving and cynical purpose, and yes they're of course also very much part of the problem and not the solution. But it doesn't make them wrong: sometimes it takes a vulture to tell you something is dying.

Introducing a limited preview of GPT-5.6 Sol, our next generation frontier model, as well as GPT-5.6 Terra, a balanced model for efficient, everyday work, and GPT-5.6 Luna, a fast and affordable model for high-volume work. openai.com/index/previewi…

@Scaramucci That was, very good. I knew of you superficially - ready to adjust the view.

@mattpressberg Not a soccer fan but would have loved to see some matches with the kids. When I saw the ticket prices and the acrobatics required to secure the tickets and get to the games, pff - as the OP said, I’m not an ATM.

I blame FIFA for this. The US is a mass affluent country where wealthy people can afford pricey tickets but are generally sensitive to ripoffs. FIFA is pricing this for the type of country with a small hereditary elite class who is comfortable with being treated as human ATMs.

@johnofgauntlet @godspeed_aflame What the fuck? Is this just a hot take for engagement?

@godspeed_aflame Guns of August

sometimes I'll hear about an interesting sounding history book, and then I do some more research and learn that historians actually consider it the stupid book for morons that you should only read if you want to be wrong about everything

@Grady_Booch Cybersecurity too. Re-learning the lessons on a speed run.

It is a source of continuous delight to watch the AI community rediscover the fundamentals and the dynamics of software engineering as they take those things and embellish them with AI adjectives, making them sound all fresh and new and sparkly while in truth, those fundamentals remain, well, fundamental. Remove AI from the discourse below, and what Andrew promotes are things one heard all the time as we saw - starting decades ago - the transition from assembly language to FORTRAN and COBOL, from structured to object-oriented, from waterfall to agile. The past, as is said, does not repeat itself but rather rhymes. Don’t get me wrong: I celebrate what Andrew et al are doing: developing software-intense systems that are meaningful and that endure requires intention and discipline, and I embrace that. Two dangling threads before I close: I don’t grok the semantics of “traditional teams”. The cosmos of computing is so wide and deep and diverse and crosses so many domains, I conclude that “traditional teams” is what one says when their experience is in a relatively narrow space, and they are witnessing a shift from what they grew up with in the Valley in particular, where web-centric systems of global elastic scale remain the primary focus. Second, I am dismayed at the focus on speed. If you are driving head long Thelma and Louise style toward an IPO then certainly speed will be a critical factor. But for most of the domain of computing, for systems that are meaningful and that endure, other factors are far more important: correctness, repeatability, safety, maintainability, these dominate, and as such, don’t be distracted by the noise and smoke and heat and light of an AI first style that may get you out of the starting gate quickly, but will fail you in the ultra marathon of most development.

@joakimbook @allenf32 Ability to explain things using plain and clear language is a skill, especially in the LLM era. That writing does not exhibit that skill. Extremely self important. Fine I’ll give it another go when I have more time and will report back . Send a rescue party if I don’t.

@joakimbook @allenf32 Forced myself to get through the first 10%: false dichotomies, straw men, convenient assumptions. Clear agenda from the start. I want my time back.

Holy fuck. I mean, I know @allenf32 is good and everything he touches turns into gold, but MY GOD, this might be the best thing I've ever seen him do. So eloquent, so comprehensive, so punchy, so serious. 10/10.

@radmadvlad What do you do for segmentation and isolation within the lab?

Whole homelab is in this one machine now. 12900ks 96gb ddr5 6000 Rtx3090 4tb nvme 2x14tb hdd running zfs Migrated my unraid fully with dockers and vms running in arch now.

Speaking plainly and clearly will be a talent in the AI era. Tell me what you’re talking about in 3-4 sentences. Then we can get into details.

@Amank1412 Why not get the abstract syntax tree out of the compiler and operate on that.

Someone built a tool that converts your entire codebase into a graph database. Instead of dumping code into LLMs, AI can navigate functions, classes, and dependencies like a map. It's called CodeGraphContext.

@karpathy We should all revisit the classic paper "On Trusting Trust" from Ken Thompson dl.acm.org/doi/10.1145/35… . When you code with a model, how do you know that a model is not inserting biased code. If you're using a model from <insert your adversary here>, does it put in backdoors?

A few random notes from claude coding quite a bit last few weeks. Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent. IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits. Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased. Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion. Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage. Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building. Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it. Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements. Questions. A few of the questions on my mind: - What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*. - Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro). - What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music? - How much of society is bottlenecked by digital knowledge work? TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.

@dlevine815 I find myself scrolling and searching for core points in between clarifications. Let me mark, pin or label responses and build an index of the conversation. Allow flushing of the chat of everything but the pinned answers to regain focus. Ie all the clarifying questions

We've got big plans to improve the core ChatGPT experience in 2026. What are some thing you'd love to see? Even small ideas welcome! Looking forward to getting them built 🙏

@chamath Don’t you have people to scam? Gettouttahere

“Show me the incentive and I’ll show you the outcome…”

@anton_chuvakin @ZackKorman Question is how many default to “for you” and prune aggressively vs. the accounts that they follow feed. My guess is that the former wins (just a guess)

@ZackKorman Frankly, I did an AMA here once and got NO QUESTIONS, this scarred me for life. My ego was just bruised. I see people get 400 questions an hour, and I got maybe a few, as I recall.

Should I do some kinda #AMA here or are AMAs not a thing anymore?

@anton_chuvakin Hmm, /r/cybersecurity (broad, but big), r/netsec, r/sysadmin. Have to mention r/blueteamsec but it’s a small audience

@ThreadState OK, a fair point. Maybe this is why mine failed here. But where at Reddit?

Twitter/X pushing right wing content HARD right now. What happened in the last 24 hours?