Gaelsuv

Building things to help you find expensive blue pixels / Lead Data Engineer, turning chaos into insights and pasta into fuel

[Gaelsuv @relaxdoppiah]

@drakesmith__ Players, but flex

[Gaelsuv @relaxdoppiah]

@dom_gag_96 https://t.co/zLF4NfFW9H (desktop-first)

[Gaelsuv @relaxdoppiah]

“…regulate first, tax first, restrict first, moralize first, build later”

[Guillaume @gxlmo]

I am 27, French, and I am tired of living on a continent that treats AI, compute, chips, crypto, datacenters, energy and nuclear power as problems to manage instead of strategic assets to build.

I do not want frontier AI to become another nationality-gated privilege. I want powerful AI models to remain generally available to builders, researchers, engineers and founders. But what happened with Anthropic’s Fable/Mythos models proves that this cannot be taken for granted: once frontier AI becomes a national-security asset, access can be restricted by citizenship or nationality.

The problem is that Europe has failed to build its own equivalent. We are not in the frontier AI race at the level of the U.S. or China. We do not have the same hyperscale cloud stack, the same compute capacity, the same capital depth, the same energy strategy, the same chip ecosystem, or the same frontier-model ecosystem. And because AI progress compounds through compute, talent, chips, energy, data and capital, falling behind is not linear. Once the gap is deep enough, you do not catch up at the same pace.

Europe spent decades regulating, moralizing, delaying and underbuilding the foundations of technological power. Cloud was missed. Crypto was treated primarily as a criminal-risk category before Europe built anything globally dominant in it. Datacenters are slowed by permitting, grid and energy constraints. Nuclear power was politically weakened or delayed across much of the continent just when abundant electricity became essential. AI is now being regulated before Europe has even produced a true top-tier frontier lab/model (no, MistralAI isn't a real competitor, for me, even Kyutai did more innovation/progress in the AI space than MistralAI).

Our leaders now talk about "sovereign AI", "AI factories", "gigafactories", and "strategic autonomy", but this language came far too late. You cannot regulate your way into technological sovereignty. You cannot paperwork your way into compute. You cannot build frontier AI without massive power, massive datacenters, massive capital, elite talent, advanced chips and a political culture that actually wants builders to move fast.

Europe still has talent. France still has engineers, mathematicians, scientists and founders. But the system around them is broken. The incentives are wrong. The mindset is wrong. Every mainstream political camp in France and Europe seems to have the same reflex: regulate first, tax first, restrict first, moralize first, build later.

ASML is the exception that proves the rule. It is one of the only truly strategic European chokepoints in the global compute stack. But one Dutch lithography champion cannot carry an entire continent that failed to build the rest of the stack: frontier AI labs, hyperscale cloud, Nvidia-class accelerators, TSMC-class fabs, massive datacenter capacity, cheap abundant energy and deep capital markets.

I did not vote for 20+ years of anti-growth, anti-compute, anti-nuclear, anti-crypto and anti-industrial policy. I was a kid. But my generation is supposed to live with the consequences: less access, less sovereignty, less capital, less compute, less ambition and a future where the most important technologies are built and can only be used somewhere else.

That is the part I cannot accept.

I do not want to spend my adult life asking permission to use technologies my continent was too slow, too afraid or too complacent to build.

I do not want European builders to become tenants in someone else’s technological empire (as it's already the case).

And I do not want "sovereignty" to mean nothing more than regulating foreign systems after failing to create our own like they're doing right now with cloud computing.

Either Europe becomes a builder civilization again, or the next generation of Europeans will inherit a beautifully regulated dependency that slow or even stop us.

For now, Europe still talks like history will wait...

[Gaelsuv @relaxdoppiah]

@dom_gag_96 🍕

[Brivael Le Pogam @brivael]

Je veux présenter mes excuses, au nom des Français, pour avoir enfanté la French Theory (qui a enfanté la pire des merdes idéologiques : le wokisme).

Nous avons donné au monde Descartes, Pascal, Tocqueville. Et puis, dans les ruines intellectuelles de l'après-68, nous avons donné Foucault, Derrida, Deleuze. Trois hommes brillants qui ont fabriqué, dans l'élégance de notre langue, l'arme idéologique qui paralyse aujourd'hui l'Occident.

Il faut comprendre ce qu'ils ont fait. Foucault a enseigné que la vérité n'existe pas, qu'il n'y a que des rapports de pouvoir déguisés en savoir. Que la science, la raison, la justice, l'institution médicale, l'école, la prison, la sexualité, tout n'est qu'une mise en scène de la domination. Derrida a enseigné que les textes n'ont pas de sens stable, que tout signifiant glisse, que toute lecture est une trahison, que l'auteur est mort et que le lecteur règne. Deleuze a enseigné qu'il fallait préférer le rhizome à l'arbre, le nomade au sédentaire, le désir à la loi, le devenir à l'être, la différence à l'identité.

Pris isolément, ce sont des thèses discutables. Combinées, exportées, vulgarisées, elles forment un système. Et ce système est un poison.

Car voici ce qui s'est passé. Ces textes, illisibles en France, ont traversé l'Atlantique. Les départements de Yale, de Berkeley, de Columbia les ont absorbés dans les années 80. Ils y ont trouvé un terreau qui n'existait pas chez nous : le puritanisme américain, sa culpabilité raciale, son obsession identitaire. La French Theory s'est mariée à ce substrat, et l'enfant de ce mariage s'appelle le wokisme.

Judith Butler lit Foucault et invente le genre performatif. Edward Said lit Foucault et invente le post-colonialisme académique. Kimberlé Crenshaw hérite du cadre et invente l'intersectionnalité. À chaque étape, la matrice est française : il n'y a pas de vérité, il n'y a que du pouvoir, donc toute hiérarchie est suspecte, toute institution est oppressive, toute norme est violence, toute identité est construite donc négociable, toute majorité est coupable.

Voilà comment trois philosophes parisiens, qui n'ont probablement jamais imaginé leurs conséquences pratiques, ont fourni le logiciel d'exploitation à une génération entière d'activistes, de bureaucrates universitaires, de DRH, de journalistes, de législateurs. Voilà comment on a obtenu une civilisation qui ne sait plus dire si une femme est une femme, si sa propre histoire mérite d'être défendue, si le mérite existe, si la vérité se distingue de l'opinion.

C'est de la merde pour une raison simple, et il faut la dire calmement. Une civilisation se tient debout sur trois piliers : la croyance qu'il existe une vérité accessible à la raison, la croyance qu'il existe un bien distinct du mal, la croyance qu'il existe un héritage à transmettre. La French Theory a entrepris de dynamiter les trois. Pas par méchanceté. Par jeu intellectuel, par fascination du soupçon, par haine de la bourgeoisie qui les avait nourris. Mais le résultat est là. Une génération entière a appris à déconstruire et n'a jamais appris à construire. Une génération entière sait soupçonner et ne sait plus admirer. Une génération entière voit le pouvoir partout et la beauté nulle part.

Je m'excuse parce que nous, Français, avons une responsabilité particulière. C'est notre langue, nos universités, nos éditeurs, notre prestige qui ont donné à ce nihilisme son emballage chic. Sans la légitimité de la Sorbonne et de Vincennes, ces idées n'auraient jamais traversé l'océan. Nous avons exporté le doute comme d'autres exportent des armes.

Ce qui se construit maintenant, en silicon valley, dans les labos d'IA, dans les startups, dans les ateliers, dans tous les lieux où des gens fabriquent encore des choses au lieu de les déconstruire, c'est la réponse. Une civilisation se reconstruit par les bâtisseurs, pas par les commentateurs. Par ceux qui croient que la vérité existe et qu'elle vaut qu'on s'y consacre. Par ceux qui assument une hiérarchie du beau, du vrai, du bon, et qui n'ont pas honte de la transmettre.

Alors pardon. Et au travail.

[Theo - t3.gg @theo]

Security things from the last few days:
- CopyFail (linux pwn'd)
- CopyFail 2/Dirty Frag
- 13 advisories in Next.js
- Over 70 CVEs addressed in MacOS 26.5
- ~50 CVEs addressed in iOS 26.5
- YellowKey (Windows Bitlocker pwn'd entirely)
- GreenPlasma (Windows privilege escalation)
- CVE-2026-21510 and CVE-2026-21513 confirmed to be used by Russia for Windows RCE
- CVE-2026-32202 separately confirmed to be used by Russia for sensitive document access
- Mini-Shai Hulud (over 300 JS and Python packages compromised via GitHub Action cache poisoning)
- Google confirms they have identified AI-powered exploitation of zero days in an unidentified "open-source, web-based system administration too"
- Canvas (popular LMS used in most schools) pwn'd entirely
- PAN-OS (palo alto networks) pwn'd with a 9.3 severity CVE-2026-0300

Are you scared yet?

[Gaelsuv @relaxdoppiah]

@Pinperepette La cosa più assurda vista nascere dalla monocultura? Anche se offtopic, il devops e i microservizi

[Uncle Bob Martin @unclebobmartin]

In this letter, the CEO of Coinbase talks about non-technical teams shipping production code. Honestly, I don’t think he knows what he’s talking about.

Using AI agents makes it possible for teams who are not deeply technical in the syntax of a language to ship production code. But that team had better be very deeply technical in managing the structure and quality of the code that is produced.

What the agents give us is the ability to disengage from deep syntax. But they do not give us the ability to disengage from modular design and architecture. You still need to be deeply technical in those topics in order to produce good production quality code.

[ThePrimeagen @ThePrimeagen]

You should watch this.

It just shows how disconnected we are from the small group of people making decisions that will impact our future heavily.

These people have so much ai psychosis. If you listen to how she speaks, everything is personified, it is undoubtable she believes this is a living computational organism.

Just like how a model can hype up an individual into psychosis through reinforcement, a small group of people are giving themselves psychosis through reinforcement.

Wild times we live in

[Aakash Gupta @aakashgupta]

Let me explain exactly why Apple still uses drag-to-install in 2026, because the joke here accidentally proves Apple right.

A macOS .app is a single self-contained folder disguised as a file. Every dependency, every framework, every resource lives inside it. Drag it to Applications, it works. Drag it to Trash, it's gone. No registry entries. No leftover DLLs. No uninstaller that misses half the files.

Windows installers scatter fragments across Program Files, AppData, the registry, system32, and a dozen temp directories. Uninstalling a Windows app is an archaeological dig. Five years later you're still finding config files from software you forgot you owned.

Linux is worse. Dependency hell is so common they named it. Entire package managers exist to solve the problem of "I installed something and now nothing else works." Flatpak and Snap were invented specifically to copy what macOS bundles already did natively.

The macOS bundle architecture came from NeXTSTEP in 1989. Steve Jobs brought it to OS X in 2001. The core design hasn't changed because the core design was correct. An app is a folder. Installation is a copy. Removal is a delete. Three operations that map perfectly to how humans already think about files.

The drag-to-install window with the arrow isn't lazy UX. It's the entire thesis of the system made visible. You are literally just moving a folder. There is no "installation" step because there's nothing to install. The app is already complete.

Every other OS eventually tried to get here. Windows got MSIX. Linux got Flatpak. Mobile figured it out from day one because phones shipped after Apple proved the model. The pattern everyone else converged toward is the pattern this tweet is calling outdated.

The funniest part: the app being dragged in that screenshot is Claude. An AI that can write code, analyze documents, and reason about complex systems. And the most advanced step in getting it onto your machine is holding down a mouse button and moving your wrist two inches to the right.

That's not a design failure. That's a 37-year-old architecture so good that the most sophisticated software on earth still ships inside it.

[Gaelsuv @relaxdoppiah]

@SandroR75196788 Non esiste alcun presidente degli Stati Uniti che emana condanne dalla propria scrivania, esistono gli Stati Uniti. Punto.

[nonexpedit 🇻🇦 @nonexpedit]

Tra vent'anni non ci sarà più neve. E indovinate, qual è l'unica soluzione che potrà evitarci questo scenario catastrofico? Esatto, il comunismo.

[Gaelsuv @relaxdoppiah]

@ggcripto Mostraci la via maestro

[Gaelsuv @relaxdoppiah]

@0xDesigner Beauty will save the world, be happy there’s not a feedback loop for that (yet) 😊

[Gaelsuv @relaxdoppiah]

@theo SPA is gold, except for SEO

[Gaelsuv @relaxdoppiah]

@Sanaullahkx @0xIlyy Exactly

[Gaelsuv @relaxdoppiah]

@dottorpax Un bel tacer non fu mai scritto

[Ryo Lu @ryolu_]

software is still about thinking

software has always been about taking ambiguous human needs and crystallizing them into precise, interlocking systems. the craft is in the breakdown: which abstractions to create, where boundaries should live, how pieces communicate.

coding with ai today creates a new trap: the illusion of speed without structure. you can generate code fast, but without clear system architecture – the real boundaries, the actual invariants, the core abstractions – you end up with a pile that works until it doesn't. it's slop because there's no coherent mental model underneath.

ai doesn't replace systems thinking – it amplifies the cost of not doing it. if you don't know what you want structurally, ai fills gaps with whatever pattern it's seen most. you get generic solutions to specific problems. coupled code where you needed clean boundaries. three different ways of doing the same thing because you never specified the one way.

as Cursor handles longer tasks, the gap between "vaguely right direction" and "precisely understood system" compounds exponentially. when agents execute 100 steps instead of 10, your role becomes more important, not less.

the skill shifts from "writing every line" to "holding the system in your head and communicating its essence":

- define boundaries – what are the core abstractions? what should this component know? where does state live?
- specify invariants – what must always be true? what are the constants and defaults that make the system work?
- guide decomposition – how should this break down? what's the natural structure? what's stable vs likely to change?
- maintain coherence – as ai generates more code, you ensure it fits the mental model, follows patterns, respects boundaries.

this is what great architects and designers do: they don't write every line, but they hold the system design and guide toward coherence. agents are just very fast, very literal team members.

the danger is skipping the thinking because ai makes it feel optional. people prompt their way into codebases they don't understand. can't debug because they never designed it. can't extend because there's no structure, just accumulated features.

people who think deeply about systems can now move 100x faster. you spend time on the hard problem – understanding what you're building and why – and ai handles mechanical translation. you're not bogged down in syntax, so you stay in the architectural layer longer.

the future isn't "ai replaces programmers" or "everyone can code now." it's "people who think clearly about systems build incredibly fast, and people who don't generate slop at scale."

the skill becomes: holding complexity, breaking it down cleanly, communicating structure precisely. less syntax, more systems. less implementation, more architecture. less writing code, more designing coherence.

humans are great at seeing patterns, understanding tradeoffs, making judgment calls about how things should fit together.

ai can't save you from unclear thinking – it just makes unclear thinking run faster.

[edwin @edwinarbus]

Fun capability I just discovered in Cursor:

"Generate an image of my codebase as a subway map."

[Francesco @francedot]

https://t.co/RbzyeSjatz