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Duration 14 hours (2 days)
Course Outline
Introduction to Advanced Cursor Capabilities
- Examining Cursor’s extensibility and underlying architecture
- Reviewing various AI model types and their integration points
- Configuring the environment for advanced customisation
Principles of Effective Prompt Engineering
- Crafting prompts for precision, consistency, and adaptability
- Structuring context hierarchies and managing variable injection
- Assessing prompt outputs and iterating for refinement
Building and Managing Prompt Templates
- Creating reusable prompt templates for team collaboration
- Versioning and maintaining template repositories
- Integrating prompt templates with CI/CD pipelines
Integrating Cursor with Internal Knowledge Bases
- Connecting to documentation APIs and internal data sources
- Embedding domain-specific knowledge into AI prompts
- Automating updates and synchronisation for dynamic data
Fine-Tuning Models for Domain-Specific Code Generation
- Identifying suitable use cases for fine-tuned models
- Collecting and curating datasets for fine-tuning
- Testing, validating, and deploying custom-trained models
Developing Custom Tools and Adapters
- Extending Cursor with API-based custom tooling
- Creating secure adapters for enterprise workflows
- Implementing custom actions within the editor interface
Security, Governance, and Performance Optimization
- Ensuring the secure handling of AI-generated code
- Establishing policy guards and compliance filters
- Optimising performance and resource management
Future-Ready AI Development Strategies
- Evaluating emerging Cursor features and APIs
- Adopting continuous fine-tuning and prompt lifecycle management
- Building internal frameworks for sustainable AI engineering
Summary and Next Steps
Requirements
- Robust knowledge of programming and software architecture
- Practical experience with AI-assisted coding tools and APIs
- Familiarity with machine learning principles or prompt engineering concepts
Target Audience
- AI engineers architecting custom AI workflows
- Platform and tooling engineers developing internal developer utilities
- Senior developers implementing domain-specific AI models