OpenAI caused something of a stir over the weekend when it announced plans to cut Cursor’s direct access to OpenAI models in November.

The reason? Elon Musk.

In a statement issued late on Friday, OpenAI pointed to two previous incidents involving Musk’s companies: Twitter breaking the terms of a data-licensing deal after Musk’s 2022 takeover of the social network, and Musk’s admission under oath earlier this year that xAI had partly used OpenAI models through distillation — conduct OpenAI says violated its terms of service. And now that SpaceX’s $60 billion deal to acquire Cursor has closed, OpenAI’s attentions are turning to Cursor.

“This decision was incredibly tough, as we care deeply about our models being broadly available for developers,” the company wrote. “We are making this choice because we cannot be confident that SpaceX will use our technology within our terms of service, based on our experience with Elon Musk’s companies violating contracts.”

While that in itself was big news for anyone following the day-to-day rough and tumble of the AI industry, what was particularly notable was the response of OpenAI’s arch rival.

The Anthropic factor

As The New Stack noted in its coverage, Anthropic co-founder and “chief compute officer” Tom Brown moved fast, posting publicly within hours of OpenAI’s statement to confirm that it continues to see Cursor as a “trusted partner,” and will “continue to increase compute to support Claude models in Cursor.”

Cursor has been a trusted partner of Anthropic since Sonnet 3.5. We’ll continue to increase compute to support Claude models in Cursor and are excited for what comes next with them at SpaceX.

— Tom Brown (@NotTomBrown) August 29, 2026

But anyone who has followed Anthropic’s recent history could be forgiven for wondering why.

Take Windsurf. In May 2025, reports emerged that OpenAI was in talks to buy the AI coding tool for $3 billion. Anthropic didn’t hang around for the deal to close though, and within weeks, Windsurf said Anthropic had cut its direct access to Claude 3.5 Sonnet and Claude 3.7 Sonnet.

Speaking at an event hosted by TechCrunch shortly after, Anthropic co-founder Jared Kaplan said that “it would be odd” for Anthropic to be selling Claude to OpenAI. As things transpired, the OpenAI deal fell through, and Google stepped in instead, paying $2.4 billion to hire Windsurf’s founders and R&D staff into DeepMind.

“They cut them off ruthlessly when RUMORS of OpenAI potentially buying Windsurf surfaced.”

In a social media post published on Sunday, Gergely Orosz, engineer and author of the Pragmatic Engineer newsletter, is quick to highlight the episode with Windsurf, which he noted had also been a “trusted partner” with Anthropic for some time. “They cut them off ruthlessly when RUMORS of OpenAI potentially buying Windsurf surfaced,” Orosz writes. “Now, SpaceX, an Ant(hropic) competitor bought Cursor — it’s still a trusted partner?”

Then there’s xAI, the AI company Musk founded in 2023 to build Grok, which SpaceX acquired outright in a February transaction valuing xAI at $250 billion. In January this year, Kylie Robison reported that Anthropic had cut xAI staff off from Claude, which they’d been accessing through Cursor — with Cursor reportedly telling xAI it was “a new policy anthropic is enforcing for all its major competitors.”

So Anthropic has previous form for moving fast, on rumor alone in Windsurf’s case, whenever a customer starts to resemble a competitor. Which makes this week’s public vote of confidence for a company now wholly owned by one of Anthropic’s actual rivals worth a second look.

The compute dependency

What makes SpaceX different from the previous Windsurf and xAI episodes is that Anthropic is also buying a huge amount of compute from it.

On May 6, Anthropic announced it had secured the entire output of SpaceX’s Colossus 1 data center near Memphis, Tennessee — more than 300 megawatts of compute and over 220,000 Nvidia GPUs. Anthropic had been hampered by limited compute availability, and the SpaceX deal, alongside other recent compute agreements, let it raise usage limits for Claude Pro and Max subscribers almost overnight.

Two weeks later, the financial terms came out. Per SpaceX’s IPO filing, Anthropic agreed to pay $1.25 billion a month for compute across Colossus and Colossus II — about 325,000 Nvidia GPUs combined — scheduled to run through May 2029, subject to termination rights.

SpaceX, for its part, said the arrangement would allow it to monetize some of its compute capacity while retaining enough to meet its own AI training and inference needs. As The New Stack reported in May, the deal also underscored just how central access to compute had become to competition between the leading AI labs. And it created an unusual commercial relationship: Anthropic was now buying a huge amount of compute from a company that also owned one of its direct AI rivals in xAI.

And that is what makes Anthropic’s response to the Cursor acquisition so notable. In response to Tom Brown’s post on X on Saturday, Replit founder and CEO Amjad Masad points to the contrast between Anthropic’s support for Cursor now and its treatment of Windsurf last year, suggesting the latter had been harsher than OpenAI’s decision to cut Cursor off.

“More likely answer is that you can’t do that here because you need the compute.”

“Maybe you changed your ways, but we all remember what you did to Windsurf, which was infinitely nastier,” Masad writes. “More likely answer is that you can’t do that here because you need the compute.”

Orosz essentially makes the same argument. If Anthropic was prepared to cut access when Windsurf merely looked likely to end up in OpenAI’s hands, why is it publicly promising MORE Claude capacity to Cursor after the company had actually been acquired by SpaceX?

“SpaceX basically in this enviable position where one of its biggest competitors depends on its compute infra!”

“Either SpaceX and Grok are not competitors to Anthropic (they are!); or, more likely, SpaceX leasing its Colossus 1 data center is more important to Anthropic than to stop offering Claude to SpaceX,” Orosz writes. “SpaceX basically in this enviable position where one of its biggest competitors depends on its compute infra!”

And so this effectively highlights how strong a position SpaceX finds itself in. It now owns xAI and Cursor, putting it in direct competition with Anthropic in foundation models through Grok and in AI coding tools through Cursor, while Anthropic is simultaneously paying it billions of dollars for compute capacity supporting Claude.

Whatever the stated rationale for treating Cursor as a “trusted partner,” that relationship leaves SpaceX with something neither Windsurf nor xAI had at the time Anthropic moved against them: a source of leverage over any decision on whether or not to cut access to Claude.

The post SpaceX is in an “enviable position”: why Anthropic is sticking with Cursor as OpenAI cuts access appeared first on The New Stack.

Connecting an AI agent to a tool is relatively straightforward. Things get more complicated once an organization has hundreds or thousands of resources spread across different clouds and platforms. Agentic Resource Discovery, or ARD, is designed to help agents navigate all of that.

AWS highlighted the open specification in its August 31 Weekly Roundup after taking a deeper technical look at it a week earlier, describing the idea as “DNS, but for agents.” Instead of telling an agent where to find everything in advance, ARD lets it search across different registries for what it needs.

And despite AWS highlighting the project, ARD isn’t an AWS technology. It was authored by Junjie Bu of Google, R.V. Guha of Microsoft, and Shaun Smith of Hugging Face, and released under the Apache 2.0 license. Engineers from several other companies have helped shape the project, including Cisco, Databricks, GitHub, GoDaddy, Nvidia, Salesforce, ServiceNow, and Snowflake.

AWS’s role, at least so far, has been to provide feedback on the specification and explore how it could work with its own Agent Registry. The goal is to make the existing registries work together.

Instead of telling an agent where to find everything ahead of time, ARD lets it search across different registries for what it needs.

MCP skips the discovery step

The Model Context Protocol has become a common way for AI applications to connect to external tools and data, but it assumes the client already knows which server it wants to use. That becomes a problem as companies spread their infrastructure across clouds, SaaS platforms, and internal systems.

ARD helps an agent find a resource before it tries to use it. The specification uses the term “agentic resource” to refer to anything an AI client can connect to, from an MCP server to other external capabilities. An ARD-compatible service keeps track of what’s available, rather than requiring developers to set up every connection in advance.

The Model Context Protocol has become a common way for AI applications to connect to external tools and data, but it assumes the client already knows which server it wants to use.

Federation without forced migration

Companies can keep their own catalogs and policies while routing searches to other ARD-compatible services. An enterprise, for example, could keep internal resources private while searching approved external catalogs when needed. AWS calls this “describe once, discover everywhere.”

The current v0.91 proposal, dated August 26, uses JSON-LD and a REST interface. Its required POST /search endpoint searches by task, while optional endpoints allow clients to browse available resources.

Each discovery service can set its own rules for what it returns and which sources it trusts. This is also where AWS’s DNS comparison falls short. A domain name points to a specific location, while an ARD search could turn up several options that all appear capable of doing the job.

Route 53 engineers shaped ARD

The DNS comparison has some history behind it. Two of the three authors of AWS’s August 24 ARD post work closely with Route 53. Principal software engineer Jeffrey Damick focuses on DNS and networking technologies. At the same time, Bhargav Talluri leads product management for Route 53 and for agent identity and discovery in AWS Agent Registry.The

Agent Registry already provides AWS customers with a central view of their resources. Adding ARD could bring resources running elsewhere into that view without requiring companies to register everything with AWS.

Adding ARD could bring resources running elsewhere into that view without requiring companies to register everything with AWS.

ARD’s governance is still being worked out, with board terms and membership among the details yet to be settled. The group has also discussed eventually moving the project to a neutral organization such as the W3C or an AI foundation.

Finding tools before using them

AWS is already exploring how it could connect with Agent Registry and find resources outside its own catalog.

There may not be much time to settle on a common approach, since connecting all these directories will only get harder once companies have built their own discovery systems.

The post MCP was supposed to solve the agent tooling problem. It missed a step. appeared first on The New Stack.

SpaceX and Nvidia say they are adapting the Vera Rubin NVL72 rack-scale AI platform for orbital use, with SpaceX targeting a first launch in the fourth quarter of 2027. 

The dream of an AI data center in space lives on in SpaceX and Nvidia’s August 24 announcements that the platform for Low Earth Orbit (LEO) Starmind AI satellites will be based on the Vera Rubin NVL72 chip family and architecture.

This proposed system would form the computing core of SpaceXAI’s first-generation Starmind AI satellite and extend Nvidia’s architecture from terrestrial AI data centers into space. 

SpaceX CEO Elon Musk posted on X the same day, “SpaceX, in partnership with Nvidia, has designed a space-optimized Vera Rubin NVL72 system for launch to orbit in Q4 next year, with significant scale in 2028.”

SpaceX, in partnership with Nvidia, has designed a space-optimized Vera Rubin NVL72 system for launch to orbit in Q4 next year, with significant scale in 2028 https://t.co/qdDq8YBkzl

— Elon Musk (@elonmusk) August 24, 2026

Musk’s post came after he said during SpaceX’s Q2 earnings call, “Going forward, we’ve decided to build exclusively on Nvidia because we think the Vera Rubin architecture is the best architecture.” Musk continued, “This is not some sort of far-future, distant thing; we expect to start launching these next year. We think the design of the NVL72 VR computer is a much better design than, say, having a standard rack -style design. So we expect to deploy this on the ground as well as in orbit, because we think it’s going to be a radical simplification of the standard NVL72 rack. It will cost less. It will be more effective. If we’re going to put it in space, why not want to put it on the ground? I think that’s going to be pretty cool.”

On Earth, the Vera Rubin NVL72 is Nvidia’s rack-scale AI design that combines 72 Rubin GPUs and 36 Vera CPUs, alongside high-speed networking components such as ConnectX-9 SuperNICs. Nvidia says SpaceXAI’s planned Starmind satellite will be based on an optimized version of that system.

A conventional NVL72 rack assumes gravity, technicians, stable grid power, a building-scale liquid loop and frequent replacement of failed parts. Orbit removes each of these assumptions.

The idea is more ambitious than putting a conventional edge-AI accelerator aboard a spacecraft. Nvidia and SpaceXAI are proposing to bring a modified architecture used in AI data centers into orbit, while altering it for orbital operational requirements.

Getting that working in orbit, though, is easier said than done. 

As Curtis Pyke, founder of Kingy AI, writes, “A conventional NVL72 rack assumes gravity, technicians, stable grid power, a building-scale liquid loop and frequent replacement of failed parts. Orbit removes each of these assumptions.“

“Cooling is unforgiving. Space is cold, but vacuum does not carry heat away through convection.”

In particular, Pyke continues, “Cooling is unforgiving. Space is cold, but vacuum does not carry heat away through convection. Heat must travel from the chips to the radiator surfaces and then leave as infrared radiation. SpaceX says AI1 can avoid chillers, cooling towers and fans and reduce cooling overhead by an order of magnitude.”

SpaceX explains that AI1 would instead use closed-loop liquid cooling inside the spacecraft and large deployable radiators to send heat directly to space as infrared radiation. While the claimed reduction is physically plausible in principle, there’s no proof yet that these AI satellites’ cooling systems can deliver. 

Another major problem that remains unaddressed is how to make the orbital rack radiation-tolerant. Making Vera Rubin NVL72 radiation-tolerant means far more than putting an ordinary NVL72 rack in a shielded satellite enclosure. It would require a system-level redesign of its GPUs, CPUs, memory, networking, power, cooling, firmware, and operations around a specified orbit and mission life.

LEO orbit is not benign. NASA cites typical trapped-particle dose rates of 100 to 1,000 rad(Si) per year for low-inclination LEO spacecraft below 500 km. That level of radiation is not an immediate death sentence for electronics, but over a multiyear mission it will cause cumulative degradation. Radiation-qualified space hardware can deal with that. Commercial Off-The-Shelf (COTS) electronics are another matter. A true radiation-hardened Rubin GPU would also require design changes at the transistor and circuit levels. 

Even were Nvidia to make such a chip, for a high-density AI system such as the SpaceX design, the concern isn’t simply whether one processor survives a 5- or 10-year dose. The satellite contains numerous radiation-sensitive elements, such as GPU logic, SRAM caches, register files, system memory, and memory controllers. With thousands of cores and billions of memory storage cells, the aggregate fault rate — not the behavior of an individual component — drives the design.

The most realistic near-term answer would be a radiation-tolerant, fault-managed Rubin-derived orbital system, not a fully radiation-hardened NVL72 in the traditional military-space sense. It could use selected commercial Nvidia parts, substantial shielding, ECC and data integrity mechanisms, redundant controllers and power paths, aggressive fault detection, software recovery, and reduced-performance operating modes.

The post SpaceX designed an orbital Vera Rubin. Radiation comes next. appeared first on The New Stack.