This release of Cursor's Changelog Agents, dated January 22, 2026, introduces significant enhancements focused on improving the efficiency, specialization, and transparency of AI-powered development workflows for complex, long-running tasks.

A primary innovation is the introduction of Subagents, designed to parallelize and specialize tasks. These are independent AI agents, each operating within its own isolated context, capable of being configured with bespoke prompts, specific tool access permissions, and distinct large language models (LLMs). Subagents handle discrete components of a parent agent's overall task, thereby enabling concurrent execution and reducing overall completion time. This architectural decomposition leads to more focused contextual awareness for the main agent conversation and leverages specialized expertise for individual subtasks. Cursor provides default subagents for common operations such as codebase research, terminal command execution, and parallel work stream management, while also allowing for the definition of custom subagents.

Another key feature is Agent Skills, which enable agents to dynamically discover and apply domain-specific knowledge and procedural workflows. Skills are defined in SKILL.md files, encapsulating custom commands, scripts, and instructions pertinent to particular domains or tasks. Unlike static, always-on declarative rules, skills offer a more flexible mechanism for dynamic context discovery and the execution of procedural "how-to" instructions. This approach allows agents to adapt more fluidly to various task requirements while maintaining a focused operational context, and can be explicitly invoked via a slash command menu.

The update also integrates Image Generation capabilities directly within Cursor's agent interface. Users can generate images by providing textual descriptions or by uploading a reference image to guide the underlying image generation model, specifically cited as "Google Nano Banana Pro." Generated images are presented as inline previews and are automatically saved to the project's assets/ directory. This functionality is intended for applications such as generating UI mockups, producing product assets, and visualizing architecture diagrams.

For Enterprise plan subscribers, Cursor Blame extends traditional git blame functionality with AI attribution. This feature precisely distinguishes between AI-generated and human-written code segments. For any AI-generated line, Cursor Blame provides a direct link to a summary of the originating conversation, detailing the context and reasoning behind the code's creation. It further granularly attributes AI-generated code by differentiating between outputs from Tab completions, various agent runs (broken down by the specific model utilized), and direct human edits, providing comprehensive insights into AI usage patterns across a team's codebase.

Finally, the release enhances agent-user interaction with expanded capabilities for Clarification Questions from the agent. Previously limited to Plan and Debug modes, agents can now proactively ask clarifying questions within any ongoing conversation. Critically, the agent is designed to continue processing concurrently—such as reading files, making edits, or executing commands—while awaiting the user's response, integrating the answer as soon as it becomes available. This interactive Q&A tool can also be leveraged by custom subagents and skills by instructing them to "use the ask question tool."