Cursor and SpaceX: In search of a complete loop - kwokchain

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Kevin

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April 23, 2026April 23, 2026

Cursor and SpaceX have entered an agreement to co-develop coding and knowledge agent models together. With SpaceX having the right to acquire Cursor this year for $60B or pay them $10B instead.

In coding–which is perhaps the path to general agents–being a top lab requires owning both the compute to train new models and capabilities and the product to recursively inform that process.

Both believe they are falling out of orbit. Combined they can complete the loop. Alone neither can. With this structure they can cut through a gordian knot.

The new meta

What does it take to be in the pantheon of top companies in this AI wave? Not just for a moment in time, but in the fullness of time.

There’s often debate about whether companies should be at the model or product layer. But putting aside ideal starting conditions, the growing belief is that both are eventually required. Pressure drives convergence, and this is the new meta.

A company is just a process that hopefully compounds as it scales and improves in its ability to serve customers. A company is not any specific model or product it launches. It is the machine that builds the machine. The best AI labs must establish confidence that they understand how to repeatedly build models and compound at them. And to do so requires both product and model in tandem.

Achieving the best performance requires codesigning them together. The model is trained on the harness. And only by owning the product and end customer relationships can the harness be designed to fill in the gaps in the models and then, over time, train those learnings back into the model.

The model is the product. But the harness is required to iterate the model to where it needs to go. As the model improves, the frontier of what it can be used for when supplemented by product expands too.

Being a top lab requires a dynamic equilibrium of the best models to drive your products and the best products to inform your models.

And coding is where this is playing out first.

In search of a loop

It was Anthropic that hit upon this meta with coding models and Claude Code, and every other lab has been running to catch up.

Coding (along with chat) is one of the only categories we have found that generates more than $10B in revenue a year. And it shows no signs of stopping.

But it is not just its revenue that makes coding important. It is that coding suggested this compounding agentic loop between model and product. What today takes a combination of many model calls, tools, and other work is exactly what’s needed to teach tomorrow’s models to do simply. There is no end in sight to how far this process can be taken in coding. And increasingly labs believe the path to general agents (itself a massive market or AGI depending who you ask) runs through coding models and this same process.

Being able to build state of the art coding models and products is table stakes for competing in this arena. And every lab is waking up to that.

Cursor was early to the coding market, the first to hit traction. But since then Anthropic has released Claude Code, which has taken off, and OpenAI has found its footing with Codex. Both now understand it’s essential to own the product side of coding. And the other labs are following suit, with Google and xAI both reorganizing around coding models and the need to own the product surface area.

Cursor is in an interesting position. On absolute metrics they are crushing it, growth continues unabated at ~$2B run rate. And yet Claude Code and Codex have both overtaken them, and it is increasingly clear that competing in this market requires them to build their own models. It’s rare to both be doing amazing and have everyone wonder if you are the walking dead.

Cursor must train its own models. And they’ve done this, starting with post-training an open source model in Composer 1, then extended pre-training and post-training for Composer 2, and now beginning to pre-train their own models from scratch. But it is one thing to build budget models with better margins and another to compete head to head on the state of the art. The compute expense is in the billions–if you can even get the compute.

If Cursor believes it can compete at the highest levels but will see its position degrade without matching the AI labs on compute and model training, then Elon and SpaceX are their perfect complement.

Elon merged xAI into SpaceX. Since then, its research leadership has been entirely hollowed out. A morbid joke is that it’s been like Iranian leadership: every day a new head of research is battlefield promoted, and every next day they are gone.

In recent months Elon has become convinced of the importance of coding models, moving from a small team working on them to it being the entire lab’s priority. But building a coding model from scratch without any of the data or...