Cursor has released its latest AI software development platform with a new multi-agent interface and the debut of its coding model, Composer.
The new Composer model is described as a βfrontier modelβ. Cursor claims it is four times faster than other models of similar intelligence. The company built it specifically for βlow-latency agentic codingβ within the Cursor environment. The company states that the model can complete most conversational turns in under 30 seconds.
This speed is intended to improve the developerβs workflow. Early testers reported that the ability to iterate quickly with the model was a key benefit. They also apparently grew to trust Composer for handling complex and multi-step coding tasks.
To achieve this performance, Composer was trained with a suite of powerful tools. One of the key tools mentioned is βcodebase-wide semantic searchβ. This training, Cursor says, makes Composer much better at understanding and working in large, complex codebasesβa common challenge for many generative AI coding assistants.
The second major update is the new user interface. Upon opening the new version, users will notice a βmore focusedβ design. The entire AI-driven software development experience in Cursor has been rebuilt to be βcentered around agents rather than filesβ. This change in focus is designed to allow developers to concentrate on their desired outcomes, while the AI agents manage the underlying details and code implementation.
For developers who still need to work directly with the code, the new layout retains the ability to open files easily. Users can also revert to the βclassic IDEβ view if they prefer.

A core feature of Cursorβs new platform is its ability to run many AI agents in parallel without them interfering with one another. This functionality is powered by technologies like βgit worktrees or remote machinesβ.
Cursor also noted an interesting emergent strategy from this parallel approach. They found that assigning the same problem to multiple different models and then selecting the best solution βgreatly improves the final outputβ. This is particularly effective for more difficult or complex tasks.
The company acknowledges that as AI agents take on more of the coding workload, new bottlenecks have emerged for developers. The two biggest new challenges are βreviewing code and testing the changesβ.
Cursor 2.0 includes new features designed to start solving both of these problems. The interface has been simplified to make it βmuch easier to quickly review the changes an agent has madeβ. This allows developers to dive deeper into the code only when necessary.
Cursor 2.0 also introduces a βnative browser toolβ that enables the AI agent to test its own work automatically. The agent can then iterate on its solution, running tests and making adjustments until it produces the βcorrect final resultβ. This marks a step towards a more autonomous development process, where agents can not only write code but also validate it.
See also: OpenAI unveils open-weight AI safety models for developers

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