Open-Weight Déjà Vu - by Peter Idah - The Agentic Age

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Open-Weight Déjà Vu<br>Why the battle over open-weight models looks strikingly similar to the platform transition that created the modern internet.

Peter Idah<br>Jul 26, 2026

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Jensen Huang’s post took me somewhere I never expected to go. I realised I’d seen this movie before. Only this time, the sequel is already playing out.<br>On 24th July 2026, Nvidia’s chief executive published his first-ever post on X. He didn’t use it to announce a chip or celebrate the company’s market value. He attached his name to a three-page policy letter, Open Weights and American AI Leadership, signed by an unusual coalition: Nvidia, Microsoft, Meta, Dell, IBM, Palantir, CrowdStrike, Hugging Face, Mistral, Mozilla, the Linux Foundation, Andreessen Horowitz, Y Combinator, and others. It urged Washington not to impose premature restrictions on open-weight models: systems whose trained parameters can be downloaded, inspected, modified, and run outside the infrastructure of the company that built them.<br>Thanks for reading The Agentic Age! Subscribe for free to receive new posts and support my work.

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Huang added a line of his own that wasn’t in the letter itself: “The world needs both frontier closed models and frontier open models.” That qualification mattered. Nvidia supplies the infrastructure beneath both camps. Huang was endorsing openness without declaring war on the closed labs that remain among his biggest customers. It was the careful move of a man who sells the machinery no matter which side wins.<br>A week earlier, in Shanghai, Xi Jinping had called on the world to “encourage open source, openness, collaboration and sharing” in AI. The reason this matters isn’t the language. It’s the incentive underneath it. Open models reduce the world’s dependence on American providers, and establish Chinese technology as infrastructure abroad. For thirty years, Linux, Apache, Python, Git, and Kubernetes let the rest of the world build without asking American permission first. Now China has powerful reasons to offer the same gift, on its own terms. Openness, here, isn’t the absence of strategy. It’s the strategy itself, one Xi paired, in the same speech, with a demand that AI remain “secure and controllable.” China hasn’t embraced unrestricted technological freedom. It’s recognised that offering openness is itself a form of power.<br>Between those two events sits a much more combustible dispute. Treasury Secretary Scott Bessent warned that Chinese firms could face sanctions over what he called “industrial-scale distillation attacks” on American models. Separately, the White House’s Michael Kratsios alleged that Moonshot AI had used large-scale distillation of Anthropic’s closed Fable model in building Kimi K3, extracting proprietary value at scale, not merely learning from published research. The industry letter answered without naming either company: distillation is a legitimate technique, it argued, and theft should be punished directly, not used to justify restricting an entire class of open models.<br>America is accusing China of extracting value from a frontier model. Industry is warning Washington not to confuse that theft with openness itself. That contrast, on its own, is the fight.<br>Taken separately, each of these events could be dismissed as lobbying, geopolitics, or corporate positioning. Taken together, they suggest something deeper has shifted. The most powerful supplier in the AI economy is defending open models. The head of the Chinese state is making openness part of national strategy. American companies that agree on almost nothing are warning Washington against concentrating advanced AI inside a handful of closed providers. And the leading closed-model labs are watching competitors distribute capable intelligence at a fraction of the price, with customers running it themselves.<br>Most people will read this as a debate about AI safety, Chinese competition, or intellectual property. It is a platform transition, and most people are too young, or arrived in technology too recently, to recognise what one looks like while it’s happening.<br>I trained in the United States as a Sun Microsystems Unix administrator, in an era when a serious enterprise server room had a very particular character: the hum of expensive machinery, rows of Sun, IBM, and Hewlett-Packard hardware. Solaris, AIX, and HP-UX weren’t just operating systems. They were complete institutional relationships, bundled with specialised hardware, certified engineers, vendor support, and long procurement cycles. No responsible bank was going to entrust its core workloads to software assembled by hobbyists on the internet. That was how Linux was seen well into the 1990s: interesting, useful at a university, not something a serious institution would run.<br>The dismissal wasn’t foolish. The proprietary systems were mature and accountable. Linux was fragmented, its hardware support...