Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
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 within Cascade
- Applying real-world conversation patterns for bug fixing and feature development
Predictive Edits and Multi-File Awareness
- Understanding what predictive edits are and when they trigger automatically
- Accepting, rejecting, and tuning edit suggestions across multiple files
- Automatically tracking dependencies between edited files
- Reverting cascading changes when predictions are incorrect
Terminal Integration Inside the Editor
- Opening and managing integrated terminal sessions
- How Cascade monitors terminal output to refine subsequent 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
- Differences in indexing behavior for monorepos versus single repositories
- Excluding generated artifacts and build directories to accelerate indexing
- Rebuilding the index following major structural changes
Conversational Feature Building
- Describing a feature in plain language and observing Cascade plan its implementation
- Reviewing the generated file list before accepting changes
- Running generated code immediately and feeding errors back to Cascade
- Iterative refinement through conversational follow-up prompts
Custom Rules and Technology-Specific Prompting
- Writing project-specific rules for internal frameworks
- Enforcing naming conventions via 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 of code
- 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 containing many files
- Understanding Windsurf's data handling and training opt-out options
- Configuring enterprise proxies and VPNs for regulated environments
Transitioning from Other Editors
- Importing keybindings and settings from VS Code or JetBrains
- Exporting Windsurf extensions back into standard VS Code
- Strategies for team migration 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
Audience
- Developers evaluating Windsurf as their primary development environment
- Product teams seeking native conversational AI within their editor
- Freelancers aiming to minimize context switching through terminal-in-IDE workflows
14 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 2600 € + VAT*
Contact us for an exact quote and to hear our latest promotions
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
