Cursor announced Thursday the launch of Cursor 3, a new product interface that allows users to spin up AI coding agents to complete tasks on their behalf. The product, which was developed under the code name Glass, is Cursor’s response to agentic coding tools like Anthropic’s Claude Code and OpenAI’s Codex, which have taken off with millions of developers in recent months.

“In the last few months, our profession has completely changed,” said Jonas Nelle, one of Cursor’s heads of engineering, in an interview with WIRED. “A lot of the product that got Cursor here is not as important going forward anymore.”

Cursor increasingly finds itself in competition with leading AI labs for developers and enterprise customers. The company pioneered one of the first and most popular ways for developers to code with AI models from OpenAI, Anthropic, and Google—making Cursor one of these companies’ biggest AI customers. But in the last 18 months, OpenAI and Anthropic have launched agentic coding products of their own, and started offering them through highly subsidized subscriptions that have put pressure on Cursor’s business.

While Cursor’s core product lets developers code in an integrated development environment (IDE) and tap an AI model for help, new products like Claude Code and Codex center around allowing developers to off-load entire tasks to an AI agent—sometimes spinning up multiple agents at the same time. Cursor 3 is the startup’s version of an “agent-first” coding product. According to Nelle, the product is optimized for a world where developers spend their days “conversing with different agents, checking in on them, and seeing the work that they did,” rather than writing code themselves.

Cursor is launching its new agentic coding interface inside its existing desktop app, where it will live alongside the IDE. At the center of a new window in Cursor, there’s a text box where users can type, in natural language, a task they’d like an AI agent to complete—it looks more like a chatbot than a coding environment. Press enter, the AI agent sets to work without requiring the developer to write a single line of code. In a sidebar on the left, developers can view and manage all of the AI agents they have running in Cursor.

What’s unique about Cursor 3, compared to desktop apps for Claude Code and Codex, is that it integrates an agent-first product with Cursor’s AI-powered development environment. In a demo, Cursor’s other cohead of engineering for Cursor 3, Alexi Robbins, showed WIRED how users can prompt an agent in the cloud to spin up a feature, and then review the code it generated locally on their computer.

Nelle and Robbins argue it doesn’t matter which interface developers are spending their time in—they just want people using Cursor.

Competing With the AI Labs

I visited Cursor’s office in San Francisco’s North Beach neighborhood last week. The startup is reportedly raising fresh capital at a $50 billion valuation—nearly double what it was valued in a funding round last fall—and has expanded into an old movie theater. Cursor employees used to toss their shoes in a pile by the door upon entry, but now there’s a row of large shoe racks, signaling one way in which the company is growing up.

Yet Cursor still feels like a startup. Employees tell me that’s part of the appeal of working there; the company can ship quickly and doesn’t feel too corporate. But as it finds itself racing to catch up to Anthropic and OpenAI in the agentic coding race, that scrappiness may not be enough. This battle—the one to create the best AI coding agent—may be Cursor’s most capital-intensive chapter yet.

In a major collaboration that will see the two AI companies link to the GPU manufacturer’s AI factory and AI-radio access network (RAN) ecosystem, as well as investigate research into silicon photonics technology, Marvell Technology has joined the Nvidia AI ecosystem through the NVLink Fusion platform.

The primary objective of the strategic partnership is to connect Marvell to the Nvidia universe, offering customers building on Nvidia architectures greater choice and flexibility in developing next-generation infrastructure. As part of the development, Nvidia has invested $2bn in Marvell.

Operating for more than 30 years, Marvel’s stated mission is to move, store, process and secure data with semiconductor solutions. The company believes that through a process of “deep collaboration and transparency” it is ultimately changing the way tomorrow’s enterprise, cloud and carrier architectures transform for the better.

It recognised that as more of the world’s data flows through the cloud, each cloud is unique and uses its portfolio of data infrastructure semiconductor technology to optimise the best solution for customers’ needs. Working on-premise or in the cloud, it works with customers to look for “unexpected connections” that deliver a competitive edge.

The partnership builds on Nvidia NVLink Fusion, a rack-scale platform that enables customers to develop semi-custom AI infrastructure using the NVLink ecosystem. Under the terms of the partnership, Marvell will provide custom XPUs and NVLink Fusion-compatible scale-up networking, while Nvidia will provide the supporting technologies, including Vera CPU, ConnectX NICs, BlueField DPUs, NVLink interconnect and Spectrum-X switches, as well as rack-scale AI compute.

For customers developing custom XPUs, NVLink Fusion is designed to enable a heterogeneous AI infrastructure fully compatible with Nvidia systems, allowing “seamless” integration with Nvidia GPU, LPU, networking and storage platforms while using Nvidia’s technology stack global supply chain ecosystem.

The companies will also partner to transform the world’s telecommunication network into AI infrastructure with Nvidia Aerial AI-RAN for 5G/6G, and advance networking for AI. This will include advanced optical interconnect solutions and silicon photonics technology.

“Our expanded partnership with Nvidia reflects the growing importance of high-speed connectivity, optical interconnect and accelerated infrastructure in scaling AI,” said Matt Murphy, chairman and CEO of Marvell. “By connecting Marvell’s leadership in high-performance analogue, optical DSP, silicon photonics and custom silicon to Nvidia’s expanding AI ecosystem through NVLink Fusion, we are enabling customers to build scalable, efficient AI infrastructure.”

Jensen Huang, founder and CEO of Nvidia, added: “The inference inflection has arrived. Token generation demand is surging, and the world is racing to build AI factories. Together with Marvell, we are enabling customers to leverage Nvidia’s AI infrastructure ecosystem and scale to build specialised AI compute.”

The new strategic partnership follows a similar arrangement that Nvidia struck with Nokia in October 2025. In this, the companies have announced a partnership to add the former’s AI-powered RAN products to Nokia’s RAN portfolio, enabling communication service providers to launch AI-native 5G Advanced and 6G networks on Nvidia platforms.

The aim was to drive wireless innovation in performance and efficiency, ensuring consumers using generative, agentic and physical AI applications on their devices will have “seamless” network experiences. The companies said that by working together, they were laying the strategic infrastructure and opening up a high-growth frontier for telecom providers by delivering distributed edge AI inferencing at scale.