Thomas J ThompsonThomas J Thompson • 3rd+Influencer • 3rd+ Chief Economist @ Havas | Entrepreneur in Residence @ HarvardChief Economist @ Havas | Entrepreneur in Residence @ Harvard 17h • 17 hours ago • Visible to anyone on or off LinkedIn Follow SpaceX’s Cursor Deal Signals Shift in Control of AI Workflows Bloomberg News reports that SpaceX may acquire the AI coding platform Cursor for $60 billion or invest $10 billion to deepen the partnership. The companies say they are working together to build “the world’s best coding and knowledge work AI.” This follows SpaceX’s combination with xAI, bringing AI models and compute into closer alignment with its infrastructure capabilities. Cursor is not an infrastructure company. It does not own data centers or generate compute. It sits at the application layer, shaping how developers actually work with AI. That detail matters because it reframes the move. This is not simply an expansion into software. It is a step toward controlling the interface where work is produced. For most of the past decade, progress in AI has been measured by improvements in models and access to compute. Those remain essential, but they are becoming more widely available. As that happens, differentiation starts to shift. The question becomes less about who has access to AI and more about how that access is structured and used in practice. That is where this fits. Bringing infrastructure, models, and applications closer together does not just improve performance. It can change how quickly capabilities are deployed and how consistently they are used. Over time, that can influence where value accumulates, particularly if the interface becomes the point where output is defined and measured. There is also a practical constraint running underneath this. Scaling AI requires significant compute, and compute requires energy. …
There is also a practical constraint running underneath this. Scaling AI requires significant compute, and compute requires energy. As demand increases, the ability to support that demand becomes part of the equation. Tesla, Inc. operates upstream in energy generation and storage. It is too early to draw firm conclusions about how that might connect, but it illustrates how the AI stack is extending beyond software into physical infrastructure. The reason this stands out to me is that it shifts the conversation away from what AI can do to how it is organized. That is where economic value tends to be determined. If the companies building infrastructure, models, and applications begin to align those layers more tightly, it has implications for how work scales and who ultimately captures the benefit of that scale. This is not just about one transaction. It is an example of how the next phase of AI may be taking shape, which is why it is worth paying attention to now rather than later. https://lnkd.in/gDb9sazU
On and on and on forever, just litres of #Claudorrhea dribbling from the mouths of the worst people
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