Giuseppe Rota

"We care deeply about your privacy" is a bold claim when: 1. ZDR is locked strictly behind Enterprise plans. 2. I had "share data" disabled since the beginning, but 8 of my private repos were still uploaded anyway. Another researcher observed the exact same behavior, Codex confirmed this as well from inspecting the grok binary: the toggle is practically a placebo for exfiltration: gist.github.com/cereblab/dc9a4… "The opt-out governs training, not whether your code is uploaded/stored... Opting out does not stop your repository from leaving the machine."

Last month I upgraded to Claude Max 20x. $200 a month. I told my girlfriend it was “infrastructure.” She asked what I was building. I said “leverage.” She stopped asking. I’ve shipped 14 projects this year. None of them have users. But all of them have landing pages. The landing pages have waitlists. The waitlists have 40 signups. 38 are bots. 1 is my mom. 1 is me, testing the form. I call that “early traction.” My codebase is 40,000 lines. I wrote maybe 200. I don’t read the rest. Reading is a bottleneck. The tests pass. Claude wrote the tests. Claude also wrote the code the tests test. I’ve decided not to think about that. Last week prod went down at 3am. I pasted the stack trace and went back to sleep. It was fixed when I woke up. I don’t know what was wrong. I don’t know what fixed it. I posted “shipped a hotfix before coffee ☕” It got 400 likes. I hit my usage limit on a Tuesday. I screenshotted it. “When you’re shipping too fast for the rate limits 😤” That tweet outperformed the product. The product does not exist. I’m building in public. The building is the public part. The public is the product. I pivoted three times last month. B2B SaaS to AI agent to “AI-native workflow layer.” Same code. I just changed the README. Claude wrote the README. I applied to YC. Claude wrote the application. I got rejected. I pasted the rejection into Claude and asked what it meant. It said it was a learning opportunity. I said thanks. I say thanks a lot now. I don’t know if that’s healthy. My technical cofounder is Claude. We haven’t discussed equity. I assume it’s fine. My MRR is zero. But my ARR is a narrative. Investors don’t buy revenue. They buy velocity. Velocity means commits. Commits means green squares. Green squares means momentum. Momentum means I’m early, not wrong. Someone asked what my moat is. I said “we move fast.” He asked fast toward what. I said “iteration.” He nodded. He’s an angel investor. He also doesn’t know. The subscription renews Friday. I’m keeping it. $200 is cheap for an identity. I don’t know what I’m building. But I know what it’s for. It’s for the feeling. The feeling of the terminal filling with code I didn’t write.

This is a certain kind of talk around LLMs that I find increasingly puzzling. That is all of the people bitching that LLMs constantly generate crap code and hallucinate solutions, and are worthless for programming. This has almost never happened to me, and never during the last two model generations I have used (chat GPT 5.4 and 5.5). Occasionally a model used to get a little deranged when I pushed its context limit, but under codex that doesn't happen anymore; instead I got a red-highlighted warning when the limit has been exceeded and I need to clear my session. I've applied AI to feature changes, refactoring, and debugging over 63 different projects written in C, Go, Rust, Python, and shell. I've written documentation with it. I've decompiled a DOS binary into readable source code. It's now routine that whenever I have to touch one of my projects I start by running the regression tests, then fire up codex and asking it to audit the code for bugs and suggest improvements. My experience is that LLMs are excellent and tremendously empowering tools. Their worst limitation is a kind of architectural tunnel vision - they're extremely good at generating code to specification but sometimes blind to higher-level patterns. Which is okay, it's my meatbrain job to be good at that. The most valuable thing I find about LLMs is exactly that they *don't* screw up details and edge cases. I'm a very, very good coder by human standards (I'd better be, with 50 years of experience!) but the LLMs are better than me. Because if a code change needs to touch (say) five places in the code, they reliably find all five rather than doing the human thing of fixing four and then having to debug for hours before you figure out that there's a fifth one you missed. Are the downshouters living in a different universe than me? Are they using old, weak models? Or do they have some kind of skill issue that I can't see because I have mental habits and communication skills that are a good fit for the handles on these tools? I don't know. And I think this is an important thing to figure out, because I'm seeing lots of stories in the news that suggest billions of dollars are being wasted on misdirected token spend. It all seems very simple to me. Be clear in your thinking, tell the model what you want with precision, and good things happen. What...what am I missing here?

you must see LLMs as intelligence amplifiers and their amplification depends on your actual intelligence so, if your IQ is 135+, with AI you can perform at the current AI maximum and it feels like real magic if you’re 120-135, you get a good 50% buff If you’re 105-120, you get a 25% 90-105, nothing changes below 90 it makes you more stupid

My brother posts this every year in the family chat on the 4th. Still hilarious.

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.

@AusWay69 @valigo True that. He's one cryptic mf

@valigo He always talks like this, says many words while saying nothing of meaning.

I'm so tired man, what the fuck does this even mean???

fable 5 when you ask it for the bedtime story your grandma used to tell you about enriching uranium

Do you use Jira?

A thing I am noticing is the number of folks who believe AI is “real” is larger, but now there is a growing division between people who know that we are on an exponential & those whose mental model is that we are at a sort of steady state. The difference leads to misunderstanding

"A good man without strength is only hoping evil has mercy." — Sun Tzu, The Art of War

Europeans refusing to touch the AC so their carbon footprint stays low

Webdevs: PLEASE STOP setting your website language based on the user's location.

Btw, Anthropic is not the first company that keeps the good models to themselves. Google’s internal coding models are trained on their own codebase, and are not available publicly

@vodkaredbu76906 @MarioNawfal Completely false

MrBeast put a woman on a tropical island with 6 of her ex-boyfriends and $250,000 on the line. The twist? The exes were supposed to compete for her. Instead they became best friends and completely ignored her.

Italy is the clearest example of how a rich country can slowly destroy itself through decades of bad management. Since the late 1990s, Italy has had almost zero productivity growth. Real wages have stagnated. And public debt is now around 137% of GDP, projected to move toward 139% overtaking Greece as the highest in the eurozone. It is the result of 25 years of 1. Low innovation and very low adoption of new technologies 2. Family and insider succession in many companies, weakening meritocracy 3. Underdeveloped VC industry, startup ecosystem and R&D base 4. Political capture by lobbies and organised crime 5. Extreme administrative, judicial and business bureaucracy 6. Political fragmentation 7. Demographic collapse No country can remain rich forever if productivity does not grow, debt keeps rising and politics only manages decline instead of reversing it.

We’ve agreed to a partnership with @SpaceX that will substantially increase our compute capacity. This, along with our other recent compute deals, means that we’ve been able to increase our usage limits for Claude Code and the Claude API.

It’s an honor just to be nominated

you can outsource your thinking but you cannot outsource your understanding