Use Cases

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Use cases

Real-world scenarios that'll help you get started quickly and see the value immediately.

  1. Bug fixing from tickets

    • Copy your Jira/GitHub issue description
    • Agent can access tickets directly with Jira tools
    • Show the broken code and error messages
    • Let AI trace the problem and suggest fixes
    • Ask for multiple solution approaches
    • Advanced: Use Bug Fix Agent for autonomous end-to-end fixing

  2. Adding new API endpoints

    • Use dev mode and follow the backend workflow
    • AI generates boilerplate (routes, controllers, models)
    • You focus on business logic and validation
    • Ask AI to double-check the implementation afterwards

  3. Repeat work with previous changes

    • Leverage @Recent changes to maintain consistency
    • "Do similar for ABCDialog/ABCScreen" - apply same patterns
    • "Integrate frontend with @Recent changes API" - connect new endpoints
    • Perfect for creating similar components or features
    • Maintains coding patterns and architectural decisions
    • Advanced: Chain multiple similar implementations efficiently

  4. Investigate issues with Git history

    • Use @Git to analyze recent changes that might cause production issues
    • "What changed in the last deploy that could affect user login?"
    • "Show me commits related to the payment flow from last week"
    • AI correlates git history with reported bugs
    • Quickly identify breaking changes and potential rollback candidates
    • Advanced: Combine with error logs to pinpoint exact problematic commits

  5. Debug user-specific errors with input analysis

    • Attach user's problematic input (CSV files, form data, API requests)
    • Include related code files for validation and processing logic
    • "Why is user getting 'Invalid format' error with this CSV?"
    • AI determines if it's a technical bug or business rule violation
    • Distinguishes between code issues vs. user input problems
    • Advanced: Generate test cases from problematic user inputs

  6. Database work made simple

    • "Add a new column for user preferences"
    • "Find all users who signed up last month"
    • "Update the schema to support soft deletes"
    • AI translates human language to SQL and migrations

  7. Code reviews and refactoring

    • Paste messy code and ask "how can this be improved?"
    • Get suggestions for breaking down large functions
    • Learn better patterns and best practices
    • Identify potential bugs or performance issues

  8. Learning new libraries / old cod

    • Open the library's .d.ts files in your editor
    • Ask AI to explain patterns and generate examples
    • Get help with complex configurations
    • Understand migration guides between versions

  9. Frontend component creation

    • Show existing components as examples
    • "Create a similar component but for user profiles"
    • Get consistent styling and prop patterns
    • Generate TypeScript interfaces automatically

  10. Documentation in your company's wiki

    • Use MCP (eg Confluence) to access your company's wiki
    • Use code for the context to generate documentation
    • Submit and let AI add/update the wiki

  11. Documentation that doesn't suck

    • Generate clear docstrings and comments
    • Write README sections when your brain is fried
    • Create API documentation from code
    • Explain complex logic in plain English

  12. Project management with Jira

    • Connect AI directly to your Jira instance
    • "Create tickets for this feature breakdown"
    • "Show me my highest priority bugs"
    • "Update sprint planning based on velocity"
    • Auto-organize backlogs and sprint planning

  13. Reference stakeholder message/conversations for context

    • Copy entire Slack threads or stakeholder discussions as reference
    • Include business requirements, user feedback, and decision rationale
    • "Here's the full Slack conversation about this feature request - implement what they're asking for"
    • AI understands not just WHAT to build, but WHY and for WHOM
    • Captures nuanced requirements, edge cases, and stakeholder priorities
    • Advanced: AI can suggest clarifying questions based on conversation gaps or ambiguities
    • Advanced: Clarify the request from stakeholder if it's feasible with current design of the system, lets AI investigate it

  14. Visualize user flow with Mermaid diagrams

    • AI often gets confused about navigation across pages and app structure
    • "Create a Mermaid flowchart showing the user journey from login to checkout"
    • "Generate a sitemap diagram for this multi-page application"
    • Include all your route files and component structure as context
    • AI maps out the complete user flow and page relationships
    • Helps identify navigation gaps, dead ends, or confusing user paths
    • Also perfect for onboarding new team members or stakeholder presentations

🧭 Quick Navigation

🏠 Main Guide - Start here for overview and guidelines
⚙️ Setup Modes - Configure your AI modes
📝 Templates - Ready-to-use planning templates

Related Modes for these use cases: