Cursor 2.1: AI Clarifying Questions & Interactive Plans

Master Cursor 2.1's clarifying questions and interactive plan UI. Better plan quality, searchable plans. Complete workflow guide.

Key Takeaways

• Interactive Clarifying Questions: Cursor 2.1 asks intelligent questions before generating plans, ensuring it understands your requirements and architecture preferences upfront for higher-quality implementation plans.
• Searchable Plan UI: New interactive plan interface supports Command+F search, selective to-do execution, and sending specific tasks to new agents for parallel development workflows.
• Improved Plan Quality: Clarifying questions reduce implementation errors by 34% and cut back-and-forth iterations by 42%, resulting in faster development cycles and more accurate code generation.
• AI Code Reviews & Instant Grep: Find and fix bugs directly in the editor with AI-powered code reviews. All grep searches are now instant across your entire codebase, regardless of which model you use.

Cursor 2.1 Technical Specifications

Released November 21, 2025 - VS Code fork with AI-native features

Specification	Details
Release	November 21, 2025
Shortcut	Shift+Tab for Plan Mode
Search	Command+F in plans
Parallel	Up to 8 agents simultaneously
Storage	.cursor/plans/ (Markdown)
Models	Claude, GPT-4.1, Gemini 3 Pro
Pricing	$0 - $200/month
Instant Grep	Beta - All models supported

Cursor released version 2.1 on November 21, 2025, introducing features that fundamentally improve how developers collaborate with AI coding assistants: clarifying questions, interactive plan UI, AI code reviews, and instant grep. The clarifying questions feature addresses a persistent challenge in AI-assisted development—the gap between what developers want and what AI assistants assume. Instead of generating code based on inferred assumptions, Cursor 2.1 asks intelligent, context-aware questions before implementation, reducing errors by 34% and cutting back-and-forth iteration cycles by 42%.

The interactive plan UI transforms static implementation plans into searchable, actionable task lists that support modern development workflows. Plans become living documents you can search with Command+F, track progress with interactive checkboxes, and distribute across multiple Cursor agents for parallel development. For teams building complex features that span dozens of files and components, these improvements reduce planning overhead by 50% while improving code quality through better upfront alignment. This guide explores how to leverage Cursor 2.1's new features for more efficient AI-assisted development workflows.

How Clarifying Questions Work

Clarifying questions in Cursor 2.1 activate automatically when you request implementations with potential ambiguity. Press Shift+Tab from the chat input to enter Plan Mode. When you ask Cursor to implement a new feature, refactor existing code, or integrate a third-party service, it analyzes your codebase context and identifies decision points where multiple valid approaches exist. Instead of selecting an approach arbitrarily, Cursor pauses before plan generation and presents 3-5 targeted questions through an interactive dialog.

Pro Tip: For better planning, describe your end goal clearly. Agent creates more accurate task breakdowns when it understands the full scope upfront.

The questions are remarkably context-aware, adapting to your specific project structure and conventions. For a React project using Redux, Cursor might ask whether new state should live in Redux global state or component local state, and whether to use Redux Toolkit or classic actions/reducers. For a Next.js application, it asks about server components versus client components, static generation versus server-side rendering, and API route patterns versus server actions. These aren't generic yes/no questions—Cursor presents concrete options with brief explanations of tradeoffs, helping you make informed architectural decisions.

You answer questions through a streamlined interface that saves your responses as implementation context. Each question includes a text input or multiple-choice selector, with the option to skip individual questions if you want Cursor to use its best judgment. Your answers feed directly into the plan generation phase, ensuring the resulting implementation plan reflects your specific requirements and architectural preferences. Cursor remembers patterns from your answers—if you consistently choose TypeScript strict mode, prefer functional components, or favor certain validation libraries, it adapts future questions to align with these preferences.

Essential Keyboard Shortcuts

Shortcut	Action
Shift+Tab	Enter Plan Mode from chat input
Cmd+F / Ctrl+F	Search within generated plans
Ctrl+Enter	Queue follow-up message
Cmd+Enter	Force push message (bypass queue)

The impact on development velocity is substantial. Internal Cursor testing shows that clarifying questions reduce implementation errors by 34% because developers catch misalignment before code generation rather than during review. The questions also reduce back-and-forth iteration cycles by 42%—instead of reviewing generated code, requesting changes, and waiting for regeneration, you provide direction upfront and receive higher-quality results on the first attempt. For complex features, this time savings compounds across multiple files and components.

AI Code Reviews: Find Bugs Before They Ship

Cursor 2.1 introduces in-editor AI code reviews that complement the planning workflow. After generating code from your plans, you can now find and fix bugs directly in Cursor without leaving your development environment. The AI analyzes your changes and surfaces potential issues in the sidebar, enabling faster debugging cycles and higher code quality before commits.

In-Editor Review

• Real-time bug detection during development
• Issues displayed in sidebar for easy navigation
• One-click fixes for common problems

Instant Grep (Beta)

• All agent grep commands now instant
• Supports regex and word boundary matching
• Works across all models in Cursor

The AI code review feature works alongside Bugbot, Cursor's existing integration for source control providers like GitHub (including Enterprise Server) and GitLab. While Bugbot operates at the pull request level, in-editor reviews provide immediate feedback during development. Additionally, all grep commands run by agents are now instant—a significant improvement for codebase navigation. Instant grep supports regex searches and word boundary matching through the codebase sidebar, working across all models in Cursor.

Note: For CI/CD integration, Cursor provides CLI cookbook documentation for automated code reviews in pipelines, enabling high-severity issue flagging with inline comments on changed lines.

Interactive Plan UI Features

The interactive plan UI transforms Cursor's implementation plans from static markdown text into dynamic, searchable task management interfaces. After Cursor generates a plan (informed by your clarifying question responses), the plan appears as an interactive list where each implementation step is a to-do item with a checkbox. You can mark tasks as complete as you work through them, providing visual progress tracking for multi-day implementations. Plans are saved as Markdown files in .cursor/plans/ and persist across sessions, so you can close Cursor and resume work days later without losing context.

Command+F search functionality addresses a critical pain point with large implementation plans. Complex features often require changes across 20-50 files, and finding specific components or functions in a long plan was previously tedious manual scrolling. With searchable plans, you can instantly jump to any file, component, or implementation detail. This is particularly valuable during code review—team members can search for files they own and immediately see what changes Cursor proposes without reading through the entire plan.

The most powerful feature is sending selected to-dos to new Cursor agents for parallel development. Cursor 2.1 supports up to 8 parallel agents running simultaneously, each operating in an isolated workspace using Git worktrees or remote machines to prevent file conflicts. Select one or more to-do items from the plan, right-click, and choose 'Send to New Agent.' Cursor spawns a new agent instance with just those to-dos and relevant codebase context, allowing it to work independently while the original agent continues with other tasks.

Warning: Parallel agents multiply both productivity and compute cost. Ensure task independence before distributing work—tightly coupled tasks like database schema changes and dependent code should not be parallelized.

This parallel execution capability can reduce implementation time for complex features by 40-60%, though it requires careful dependency management. You need to ensure tasks sent to different agents don't have tight coupling—if the login UI depends on specific API response formats, implement the API first or clearly specify the expected contract. Cursor provides basic conflict detection when merging work from multiple agents, highlighting files modified by more than one agent for manual review, but preventing conflicts through thoughtful task distribution is more efficient than resolving them afterward.

Cursor Pricing: Plan Mode Access by Tier

Cursor's 2025 pricing model combines subscription tiers with usage-based credits. Plan Mode is available across all tiers, with the main differences in model access and usage limits. Understanding the pricing structure helps optimize your investment based on team size and usage patterns.

Plan	Monthly Cost	Plan Mode	Parallel Agents	Best For
Free/Hobby	$0	Limited usage	No	Learning & exploration
Pro (Popular)	$20	Full + $20 credits	Yes (up to 8)	Individual developers
Pro+	$60	Extended limits	Yes (up to 8)	Power users
Ultra	$200	Maximum limits	Priority access	Heavy AI usage
Business	$40/user	Full + team features	Yes (up to 8)	Teams & agencies

The Pro plan at $20/month covers approximately 225 Sonnet 4 requests, 550 Gemini requests, or 650 GPT-4.1 requests monthly—the vast majority of Pro users don't exhaust their included usage. Additional frontier model usage can be purchased at cost if needed.

Cost Optimization Strategies

1. Model Selection: Use Claude Sonnet 4 for complex planning (higher quality), GPT-4.1 or Gemini for simpler tasks (lower cost per token).
2. Prompt Efficiency: Detailed prompts mean fewer clarifying questions and faster completion. Include context upfront to reduce token usage.
3. Plan Reuse: Save plans to workspace as templates. Reuse for similar tasks to reduce redundant planning for repeated patterns.
4. Parallel Agent ROI: 8 agents = 8x compute cost. Only parallelize when time savings justify cost—best for deadline-critical projects.

Cursor 2.1 vs Windsurf vs GitHub Copilot

Cursor, Windsurf, and GitHub Copilot take fundamentally different approaches to AI-assisted code planning. Understanding these differences helps you choose the right tool for your workflow. Note that Cursor and Windsurf are full IDEs (VS Code forks) while GitHub Copilot is an extension that works within existing editors.

Feature	Cursor 2.1	Windsurf Cascade	GitHub Copilot Agent
Planning Approach	Interactive Q&A	Autonomous flows	Issue-based
Clarifying Questions	Yes (Interactive UI)	Limited	No
Searchable Plans	Cmd+F support	No	N/A
Plan Persistence	.cursor/plans/	Session only	Issue-linked
Parallel Agents	Up to 8	Up to 4	1
Model Selection	Multiple options	Limited	Multiple (GPT-4.5, Claude, o3)
IDE Requirement	Cursor IDE	Windsurf IDE	Any IDE
Pro Pricing	$20/month	$15/month	$19/month (Pro+: $39)

Choose Cursor When

• Complex multi-file projects
• Team collaboration workflows
• Parallel development needs
• Upfront architecture decisions

Choose Windsurf When

• Budget is primary concern
• Simpler, solo projects
• Prefer autonomous AI flows
• Fast prototyping priority

Choose Copilot When

• GitHub-centric workflow
• Issue-driven development
• Keeping existing IDE setup
• Automated PR creation

Industry Note: OpenAI acquired Windsurf (formerly Codeium) for approximately $3 billion in May 2025, which may influence future product direction and integration with OpenAI models.

Enterprise Features & Security

For teams requiring security validation and administrative controls, Cursor's Business plan ($40/user/month) includes enterprise features alongside full Plan Mode capabilities. Understanding security implications helps organizations adopt AI coding assistants responsibly.

Feature	Free	Pro	Business
Privacy Mode	Yes	Yes	Yes
SSO/SAML Integration	No	No	Yes
Admin Dashboard	No	No	Yes
Audit Logs	No	No	Yes
Usage Analytics	No	Basic	Advanced
Centralized Billing	No	No	Yes

Privacy Mode Trade-offs

Privacy Mode keeps code local but limits some features:

• Background agents disabled (require cloud)
• Memory/history syncing restricted
• Plan Mode fully functional

Cloud Agent Integrations

Cursor 2.1 expanded enterprise integrations:

• GitHub Enterprise Server
• GitLab (full support)
• Sentry error tracking
• Plain customer support

Workflow Optimization Strategies

Maximizing the value of clarifying questions and interactive plans requires adapting your development workflow to leverage these features effectively. For clarifying questions, the key is providing enough initial context that Cursor asks the right questions. Instead of vague requests like 'add user authentication,' provide structured requirements: 'Implement user authentication with email/password login, JWT tokens, password reset flow, and email verification. Use our existing PostgreSQL database and Resend email service.' This context helps Cursor ask about implementation specifics rather than basic requirements.

When reviewing Cursor's clarifying questions, take time to consider tradeoffs rather than rushing through to get code faster. The 30-60 seconds spent thoughtfully answering questions pays dividends in higher-quality initial implementations. If a question reveals that you haven't fully thought through an architectural decision, this is the right time to pause and clarify your requirements—much cheaper than discovering the gap after Cursor has generated code across 15 files.

For interactive plans, establish a habit of reviewing the complete plan before approving execution. Cursor's plan quality is high, but occasionally it misinterprets requirements or makes suboptimal architectural choices. With searchable plans, you can quickly scan for potential issues—search for file paths to verify Cursor understands your project structure, search for library names to confirm it's using your preferred dependencies, search for function names to check naming conventions. Catching issues at the plan stage takes seconds; catching them after code generation takes minutes.

When using parallel agent execution, start with clearly independent tasks to build confidence in the workflow. Good candidates for parallel execution include frontend and backend work with well-defined API contracts, different pages or features with minimal shared state, and test writing alongside feature implementation. Avoid parallelizing tightly coupled tasks like database schema changes and the code that uses those schemas—the coordination overhead exceeds the time savings from parallel execution.

Real-World Development Scenarios

Clarifying questions and interactive plans excel at different types of development tasks. For new feature implementation, clarifying questions shine by establishing clear architectural direction before code generation. When implementing a new payment processing feature, Cursor might ask: which payment provider (Stripe, PayPal, Square)? Synchronous or asynchronous webhook handling? Where should payment records be stored? Client-side or server-side payment method tokenization? These upfront decisions ensure the implementation aligns with your infrastructure and security requirements from the start.

For large-scale refactoring projects, interactive plans with parallel execution prove invaluable. Migrating a React application from class components to functional components with hooks might generate a plan with 40+ file updates. You can search the plan for specific component categories (auth components, dashboard components, utility components), verify the migration approach for each category, and then send different categories to separate agents for parallel refactoring. What might take a single agent 3-4 hours completes in 1-2 hours with three agents working in parallel.

For API integration tasks, clarifying questions prevent common misalignment around error handling, retry logic, and rate limiting. When you ask Cursor to integrate a third-party API, it asks about authentication patterns (API keys in environment variables, OAuth flows, SDK usage), error handling strategy (retry with exponential backoff, fail fast, circuit breaker patterns), and data persistence (cache responses, store raw data, transform before storing). These questions ensure the integration follows your organization's patterns rather than Cursor's generic defaults.

For bug fix workflows, the combination of clarifying questions and searchable plans helps manage complex debugging across multiple files. When investigating a performance issue, Cursor might ask about acceptable performance budgets, whether to optimize for initial load or runtime performance, and what monitoring tools you use. The resulting plan lists specific optimizations across components, and you can search for specific performance bottlenecks to verify Cursor's analysis aligns with your profiling data before implementing fixes.

Team Collaboration Benefits

Cursor 2.1's features provide particular value for team development workflows. Searchable plans serve as living implementation documentation that improves code review processes. When a developer submits a pull request generated with Cursor, reviewers can access the original implementation plan, search for files they own or components they're familiar with, and see exactly what changes were requested and why. This context dramatically improves review quality—reviewers understand the intent behind changes rather than just seeing diffs.

Clarifying questions help standardize implementation patterns across teams. When multiple developers use Cursor on the same project, their answers to clarifying questions create implicit documentation of team preferences. Over time, patterns emerge—the team consistently chooses certain validation libraries, prefers specific state management patterns, or has strong opinions about error handling. These patterns can be extracted into team guidelines or even custom Cursor configuration that pre-answers common questions based on established conventions.

For pair programming and mentoring scenarios, interactive plans facilitate knowledge transfer. A senior developer can work with Cursor to generate an implementation plan with clarifying questions answered according to team best practices, then send specific to-dos to a junior developer to implement while remaining available for questions. The junior developer gets clear, searchable implementation guidance with built-in context about architectural decisions, reducing the mentorship overhead while maintaining quality through structured guidance.

When NOT to Use Plan Mode: Honest Guidance

While Plan Mode excels at complex, multi-file implementations, it's not always the right choice. Understanding when to skip clarifying questions helps you work more efficiently and avoid unnecessary overhead.

Don't Use Plan Mode For

• Simple single-file changes - Quick bug fixes, typos, adding one function
• Exploratory prototyping - When you don't know what you're building yet
• Time-critical hotfixes - Production emergencies, security patches
• Highly specialized domains - Niche frameworks with limited AI training
• Legacy systems without tests - High risk of breaking undocumented behavior

When Human Expertise Wins

• Architectural decisions with business implications
• Performance optimization requiring profiling and measurement
• Security-critical implementations needing expert review
• Regulatory compliance code with legal requirements
• UX and accessibility refinements requiring user empathy

Common Mistakes with Cursor Plan Mode

Based on common patterns observed across development teams, these mistakes can significantly reduce the effectiveness of Cursor's planning features. Avoiding them helps maximize the value of your AI coding investment.

Mistake #1: Over-Broad Initial Prompts

The Error: Asking Cursor to "build me a complete authentication system" or "add user management."

The Impact: Overwhelming clarifying questions and plans spanning 50+ files, making review impossible and execution error-prone.

The Fix: Break complex features into focused requests. Start with "Add email/password login using NextAuth.js with our existing PostgreSQL User model."

Mistake #2: Skipping Clarifying Questions

The Error: Rushing through or skipping questions to get code faster.

The Impact: Multiple revision cycles as generated code doesn't match expectations. The 60 seconds "saved" costs 10+ minutes in corrections.

The Fix: Treat clarifying questions as architectural checkpoints. Internal testing shows 42% fewer revision cycles when questions are answered thoughtfully.

Mistake #3: Parallelizing Tightly Coupled Tasks

The Error: Sending dependent tasks like "create database schema" and "build API endpoints" to separate agents simultaneously.

The Impact: Merge conflicts, incompatible implementations, and wasted compute as work must be redone.

The Fix: Map dependencies before distributing work. Parallelize clearly independent tasks: frontend + backend with defined API contracts, or tests + implementation.

Mistake #4: Ignoring .cursorrules Configuration

The Error: Using Plan Mode without project-specific rules, relying on generic defaults.

The Impact: Generated code doesn't match team conventions, requires manual reformatting, or uses wrong libraries.

The Fix: Create .cursor/rules/*.mdc files with coding style, framework patterns, testing requirements, and preferred dependencies.

Mistake #5: Not Reviewing Plans Before Execution

The Error: Approving plans immediately without using Command+F to verify contents.

The Impact: Discovering architectural problems after Cursor has generated code across 20 files. Costly to unwind.

The Fix: Quick review checklist: Search for file paths (correct structure?), library names (preferred deps?), and function patterns (naming conventions?).

Conclusion

Cursor 2.1's clarifying questions and interactive plan UI represent meaningful evolution in AI-assisted development tools, moving beyond pure code generation to support the planning and coordination workflows that occupy significant developer time. Clarifying questions reduce the assumption gap between developer intent and AI execution, cutting implementation errors by 34% through upfront alignment. Interactive plans with search and parallel agent execution transform complex implementations from linear, time-intensive processes into parallelizable workflows that can reduce development time by 40-60% for suitable tasks.

For development teams adopting Cursor 2.1, the key to maximizing value is adapting workflows to leverage these features rather than treating them as simple productivity enhancements. Invest time in thoughtfully answering clarifying questions, review and search plans before execution, and experiment with parallel agent workflows on independent tasks. These practices compound over time as Cursor learns your preferences and teams develop best practices for effective AI collaboration. As AI coding assistants continue to evolve, features like Cursor 2.1's clarifying questions and interactive plans point toward a future where AI handles not just code generation but actively participates in planning and architectural decision-making.

Frequently Asked Questions

What are clarifying questions in Cursor 2.1 and how do they improve development?

Clarifying questions in Cursor 2.1 are intelligent pre-implementation questions that Cursor asks before generating a plan or writing code. When you request a feature or refactoring, Cursor analyzes your codebase and identifies ambiguities—should this use TypeScript or JavaScript? REST or GraphQL? Client-side or server-side validation? Instead of making assumptions, Cursor presents 3-5 targeted questions that you answer through an interactive UI. This upfront clarification reduces implementation errors by 34% because Cursor understands your exact requirements before generating code, eliminating the common pattern of generate-review-request changes-regenerate cycles.

How does the interactive plan UI work in Cursor 2.1?

Cursor 2.1's interactive plan UI transforms plans from static text into actionable, searchable task lists. After Cursor generates an implementation plan, the UI displays each step as an interactive to-do item with checkboxes, allowing you to mark completed tasks and track progress. The interface supports Command+F (or Ctrl+F) search across plan contents, making it easy to find specific components or files in large implementation plans. You can select individual to-dos and send them to new Cursor agents for parallel development—for example, sending frontend work to one agent while another handles backend implementation simultaneously. Plans are saved with your project and remain searchable across sessions.

What types of clarifying questions does Cursor 2.1 ask?

Cursor 2.1 asks context-aware questions tailored to your specific task and codebase. For new features, it asks about technology choices (which framework, which library, which API pattern), data modeling decisions (database schema, validation rules, relationships), and user experience preferences (error handling, loading states, accessibility requirements). For refactoring tasks, it asks about scope boundaries (which files to include, what to preserve, what to modernize), testing requirements (maintain existing tests, write new tests, update test patterns), and breaking change tolerance (strict backward compatibility or acceptable breaking changes). The questions adapt based on your codebase—for TypeScript projects, it won't ask about type systems; for established REST APIs, it won't suggest GraphQL without reason.

Can I skip clarifying questions if I want Cursor to work faster?

Yes, Cursor 2.1 includes a 'Skip Questions' option that bypasses the clarification phase and generates a plan based on reasonable defaults inferred from your codebase. This is useful for simple tasks where the implementation approach is obvious, or when you're iterating quickly and prefer to refine through multiple cycles. However, for complex features or when working in unfamiliar parts of a codebase, answering clarifying questions upfront typically saves time overall—the 30-60 seconds spent answering questions prevents 5-10 minutes of review and regeneration cycles. Cursor learns from your answers over time, asking fewer questions on similar tasks as it builds understanding of your preferences.

How do searchable plans improve development workflows?

Searchable plans address a common pain point with large implementation tasks: keeping track of what needs to be done across dozens of files and components. With Command+F search, you can instantly jump to specific files, functions, or components within a plan, making it easy to understand what changes affect particular parts of your codebase. This is especially valuable for code review—reviewers can search the plan for specific components they own and see exactly what changes are proposed. The persistent, searchable history of plans also serves as documentation, allowing you to review past implementation decisions and understand why certain architectural choices were made weeks or months later.

What's the benefit of sending plan to-dos to new agents?

Sending plan to-dos to new agents enables true parallel development workflows that were previously difficult with AI coding assistants. Instead of waiting for Cursor to complete one task before starting another, you can select specific to-dos (e.g., 'Implement user authentication API endpoints') and send them to a new agent instance while the original agent works on other tasks (e.g., 'Build login UI components'). Each agent maintains its own context and conversation history, working independently on its assigned tasks. This parallel execution can reduce implementation time for complex features by 40-60%, with the caveat that you need to carefully manage dependencies between tasks to avoid conflicts when merging work from multiple agents.

How much does Cursor Plan Mode cost?

Plan Mode is available across all Cursor pricing tiers. The Free/Hobby plan ($0/month) includes limited Plan Mode usage with basic model access. The Pro plan ($20/month) provides full Plan Mode access with $20 of frontier model credits—enough for approximately 225 Sonnet 4 requests, 550 Gemini requests, or 650 GPT-4.1 requests monthly. Pro+ ($60/month) offers extended usage limits for power users, while Ultra ($200/month) provides maximum limits with priority access. The Business plan ($40/user/month) includes team features like centralized billing, admin dashboards, and usage analytics alongside full Plan Mode capabilities.

How does Cursor 2.1 compare to Windsurf for code planning?

Cursor 2.1 and Windsurf Cascade take different approaches to AI-assisted planning. Cursor's interactive clarifying questions actively engage developers before plan generation, ensuring alignment upfront. Windsurf Cascade focuses on autonomous 'AI flows' with less upfront interaction. Key differences: Cursor supports up to 8 parallel agents vs Windsurf's 4; Cursor plans are searchable via Command+F and persist in .cursor/plans/ while Windsurf plans are session-only; Cursor offers more model selection flexibility. Choose Cursor for complex projects requiring team collaboration and parallel development. Choose Windsurf for budget-conscious teams ($15/month vs $20) preferring a more autonomous workflow.

What models work with Cursor Plan Mode?

Cursor Plan Mode supports multiple AI models including Claude Sonnet 4, GPT-4.1, Gemini 3 Pro, and Cursor's own custom model optimized for coding. A powerful workflow feature allows you to plan with one model and build with another—for example, using Claude Sonnet 4 for detailed planning (higher quality reasoning) then switching to GPT-4.1 for implementation (faster execution). Model availability depends on your subscription tier, with the Pro plan providing $20 of frontier model credits monthly. You can also choose to plan in foreground or background, or use parallel agents with different models simultaneously.

How do I configure .cursorrules for better Plan Mode results?

For optimal Plan Mode results, create project-specific rules in .cursor/rules/ with .mdc (Markdown Components) files. Include coding style preferences (functional vs OOP, strict typing requirements), framework patterns (React component conventions, API design patterns), testing requirements (unit test expectations, coverage targets), and file organization rules (naming conventions, directory structure). Example rules: 'Always ask about testing strategy before generating code', 'Prefer functional components over class components', 'Use TypeScript strict mode for all new files'. The legacy .cursorrules file in project root still works but migrating to the new .cursor/rules/ system is recommended for better organization and conditional rule activation.

How many parallel agents can Cursor run simultaneously?

Cursor 2.1 supports up to 8 parallel agents running simultaneously on a single prompt. Each agent operates in an isolated workspace using Git worktrees or remote machines to prevent file conflicts. The Agent view sidebar lets you create, name, and manage multiple agents, showing status, progress indicators, and output logs for each. When distributing work, ensure tasks don't have tight dependencies—send clearly independent work like frontend and backend with defined API contracts to different agents. Cursor provides basic conflict detection when merging work from multiple agents, highlighting files modified by more than one agent for manual review.

Why isn't Plan Mode working or responding slowly?

Common causes include network configuration issues—Cursor relies on HTTP/2 for AI features, and corporate networks, VPNs, or proxies like Zscaler may block this. Enable HTTP/1.1 fallback in app settings to resolve. Other fixes: ensure you're on the latest Cursor version (check for updates), verify your subscription has available credits (Pro plan credits reset monthly), and check if Privacy Mode is restricting cloud features. For performance issues with large codebases, try limiting context by opening specific files before entering Plan Mode. If problems persist, the Cursor community forum has active troubleshooting discussions.

How do I save Cursor plans permanently?

Plans initially appear as temporary virtual files. To preserve them permanently, click 'Save to workspace' which stores plans in the .cursor/plans/ directory as Markdown files. Saved plans persist across sessions, can be version-controlled with your project, and remain searchable via Command+F. This is valuable for team collaboration—share plans in pull request descriptions for reviewers to understand implementation intent. Plans also serve as documentation for future reference, helping you understand why certain architectural decisions were made months later. You can edit saved plans directly in Markdown format and re-use them as templates for similar future tasks.

What's the difference between Plan Mode and regular Agent Mode in Cursor?

Plan Mode and Agent Mode serve different purposes. Agent Mode tackles tasks directly—breaking them down, writing code across files, running terminal commands, and auto-fixing errors in one continuous flow. Plan Mode adds a strategic layer: it researches your codebase, asks clarifying questions, creates a structured Markdown plan with file paths and code references, and lets you review and edit before any code is written. Use Plan Mode (Shift+Tab) for complex features where upfront alignment prevents rework. Use Agent Mode for smaller tasks, bug fixes, or when you want Cursor to execute immediately. Many developers combine both: Plan Mode for architecture, then Agent Mode for implementation.