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Course Outline
The Cascade Conversational Interface
- How Cascade differs from traditional chat panels in other Integrated Development Environments (IDEs)
- Maintaining conversational context across feature requests for government projects
- Switching between explain, plan, and act modes within Cascade for efficient development processes
- Real-world conversation patterns for bug fixing and feature building in public sector applications
Predictive Edits and Multi-File Awareness
- Understanding predictive edits and when they trigger automatically in government coding environments
- Accepting, rejecting, and tuning edit suggestions across multiple files for government projects
- Automatically tracking dependencies between edited files to ensure integrity
- Reverting cascading changes when predictions do not align with project requirements
Terminal Integration Inside the Editor
- Opening and managing integrated terminal sessions for streamlined development workflows
- How Cascade monitors terminal output to refine subsequent steps in government projects
- Running tests, builds, and deployments without leaving the Windsurf environment for enhanced efficiency
- Handling interactive Command-Line Interface (CLI) prompts during automated flows to maintain seamless operations
Windsurf Indexing and Context Management
- How Windsurf constructs and maintains a real-time project index for government applications
- Different indexing behaviors for monorepos versus single repositories in public sector projects
- Excluding generated artifacts and build directories to accelerate indexing processes
- Rebuilding the index after significant structural changes to ensure accuracy
Conversational Feature Building
- Describing a feature in plain language and observing Cascade plan it for government projects
- Reviewing the generated file list before committing changes to maintain project integrity
- Running generated code immediately and providing error feedback to Cascade for iterative improvement
- Engaging in iterative refinement through conversational follow-up prompts for enhanced development accuracy
Custom Rules and Technology-Specific Prompting
- Writing project-specific rules for internal frameworks to enhance customization
- Enforcing naming conventions through Windsurf rule files for consistent coding practices
- Customizing indexing for Domain-Specific Languages (DSLs) and non-standard file formats in government projects
- Sharing rule sets across a development team to ensure uniformity and efficiency
Debugging with Cascade Assistance
- Pasting stack traces into Cascade for root-cause analysis in government applications
- Requesting Cascade to compare working and broken versions of code to identify issues
- Running regression tests within Cascade's terminal watcher to ensure robustness
- Identifying hallucinated imports or missing dependencies after edits to maintain code integrity
Version Control and Review Integration
- Generating commit messages from conversational change summaries for clear documentation
- Preparing pull request descriptions via Cascade chat for seamless collaboration
- Responding to reviewer comments with targeted file edits to address feedback efficiently
- Maintaining a clean commit history during conversational development processes in government projects
Performance and Enterprise Deployment
- Managing large workspace indexing within memory constraints for optimal performance in government environments
- Optimizing startup time for repositories with numerous files to enhance user experience
- Understanding Windsurf's data handling and training opt-out options for compliance with government regulations
- Configuring enterprise proxy and Virtual Private Network (VPN) settings for regulated environments in government operations
Transitioning from Other Editors
- Importing keybindings and settings from VS Code or JetBrains to facilitate a smooth transition
- Exporting Windsurf extensions back into standard VS Code for flexible integration options
- Team migration strategies and pilot program structures for government development teams
Requirements
- Experience with an Integrated Development Environment (IDE) such as Visual Studio Code or JetBrains products
- Familiarity with version control systems like Git and agile development methodologies
- Basic experience with Large Language Model (LLM)-based chat interfaces
Audience
- Developers assessing Windsurf for government as their primary development environment
- Product teams interested in integrating conversational AI directly into their editor
- Independent contractors seeking to minimize context switching with terminal-in-IDE workflows
14 Hours
Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
