Miller describes a fast-moving few months and says SpaceX AI first gave Cursor access to its Colossus compute system while the companies explored an acquisition. Cursor had developed models including Tab autocomplete and Composer, with the goal of building a strong model for coding. After training Composer 2.5 on Colossus, the teams began working together on Grok 4.5 and Grok 4.6.
How Cursor's Browser Experience Shaped Grok Bot
Speaker
Nick Miller of SpaceX AI discusses Cursor’s evolution, its integration with SpaceX AI, and how Cursor’s browser work informed Grokbot in an interview with Callstack hosts at AgentConf 2026 in Warsaw.
Miller says the companies are still working out how to combine their products and brands. SpaceX AI brings voice, image, and video APIs, while Cursor focuses on coding tools, its desktop app, and cloud agents. He says the teams have had distinct areas of focus and are figuring out how existing Cursor and xAI customer plans might fit together.
Miller says model training has not yet reached a point where adding compute and training data stops improving results. He points to Cursor’s software development data, SpaceX engineering work, and X’s real-time information as resources that could benefit their models. Colossus gave Cursor capacity to pursue general-purpose Grok models, beyond its more narrowly focused Composer coding models.
Miller credits years of building Cursor and its tools, including a built-in browser launched in the desktop app during the prior year, with helping the team build Grokbot quickly. He says Grokbot reached internal beta in about a month and runs in an isolated virtual machine environment. The team treated browser interaction as essential so bots could work with websites even when an API or MCP server was unavailable.
Takeaways
- Distinct product strengths can make an acquisition easier to integrate while teams work out shared branding and customer plans.
- More compute can make broader model ambitions feasible, while purpose-built models may need less training data and cost less to develop.
- Experience building a product’s tools and workflows can carry over when developing a related agent.
- If an agent must work across websites, plan for browser interaction alongside APIs and MCP servers.
Mentioned in this talk
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What was claimed 13
- built
Cursor built Composer 2.5
“We finished training Composer 2.5 on Colossus”
YouTube Verified2 sources· Talk, Web· archived
- uses
“allowing us to start training on that system”
YouTube Unverified1 source· Talk
- built
“Our research and product teams have been building a model called Tab”
1:11inBuilding Cursor ComposerYouTube Verified2 sources· Talk
- built
“started collaborating with the SpaceX AI team on Grok 4.5 and then Grok 4.6”
YouTube Unverified1 source· Talk
- collaborates with
“started collaborating with the SpaceX AI team”
YouTube Unverified1 source· Talk
- acquired
“They'd officially exercised their option”
YouTube Unverified1 source· Talk
- feature
xAI: Voice, image, and video APIs“they have a suite of APIs”
YouTube Unverified1 source· Talk
- feature
xAI: Grok Build CLI tool“They have Grok Build, a CLI tool”
YouTube Unverified1 source· Talk
- feature
Cursor: Desktop app and cloud agents
“we put a lot more emphasis on the desktop app and cloud agents”
YouTube Unverified1 source· Talk
- feature
Grokbot: Computer use
“Nothing is comparable to what Grokbot can do in terms of computer use”
YouTube Unverified1 source· Talk
- metric
Grokbot: Built from day zero to internal beta in about one month
“We built Grokbot from day zero to an internal beta in about a month”
YouTube Unverified1 source· Talk
- feature
Cursor: Built-in browser in its desktop app
“We launched a built-in browser in the Cursor desktop app”
YouTube Unverified1 source· Talk
- uses
“whether there's an API or an MCP server available”
YouTube Unverified1 source· Talk







