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Course Outline
The Cascade Conversational Interface
- Understanding how Cascade differs from traditional chat panels in other IDEs
- Maintaining conversational context across feature requests
- Switching between explain, plan, and act modes inside Cascade
- Real-world conversation patterns for bug fixing and feature building
Predictive Edits and Multi-File Awareness
- Understanding what predictive edits are and when they trigger automatically
- Accepting, rejecting, and tuning edit suggestions across files
- Tracking dependencies between edited files automatically
- Reverting cascading changes when predictions miss the mark
Terminal Integration Inside the Editor
- Opening and managing integrated terminal sessions
- How Cascade watches terminal output to refine next steps
- Running tests, builds, and deployments without leaving Windsurf
- Handling interactive CLI prompts during automated flows
Windsurf Indexing and Context Management
- How Windsurf builds and maintains a real-time project index
- Indexing behavior for monorepos versus single repositories
- Excluding generated artifacts and build directories for faster indexing
- Rebuilding the index after major structural changes
Conversational Feature Building
- Describing a feature in plain language and watching Cascade plan it
- Reviewing the generated file list before accepting changes
- Running generated code immediately and feeding errors back to Cascade
- Iterative refinement with conversational follow-up prompts
Custom Rules and Technology-Specific Prompting
- Writing project-specific rules for internal frameworks
- Enforcing naming conventions through Windsurf rule files
- Customizing indexing for DSLs and non-standard file formats
- Sharing rule sets across a development team
Debugging with Cascade Assistance
- Pasting stack traces into Cascade for root-cause analysis
- Asking Cascade to compare working and broken versions
- Running regression tests within Cascade's terminal watcher
- Identifying hallucinated imports or missing dependencies after edits
Version Control and Review Integration
- Generating commit messages from conversational change summaries
- Preparing pull request descriptions via Cascade chat
- Responding to reviewer comments with targeted file edits
- Maintaining a clean commit history during conversational development
Performance and Enterprise Deployment
- Managing large workspace indexing within memory constraints
- Optimizing startup time for repositories with many files
- Understanding Windsurf's data handling and training opt-out
- Enterprise proxy and VPN configurations for regulated environments
Transitioning from Other Editors
- Importing keybindings and settings from VS Code or JetBrains
- Exporting Windsurf extensions back into standard VS Code
- Team migration strategies and pilot program structures
Requirements
- Experience with an IDE such as VS Code or JetBrains
- Familiarity with Git and agile development workflows
- Basic experience with LLM-based chat interfaces
Target Audience
- Developers evaluating Windsurf as their primary development environment
- Product teams aiming to integrate conversational AI natively into their editor
- Freelancers seeking to minimize context switching via 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
