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Kursplan
Introduction to Advanced Cursor Capabilities
- Understanding Cursor’s extensibility and architecture
- Reviewing AI model types and integration points
- Preparing the environment for advanced customization
Principles of Effective Prompt Engineering
- Designing prompts for precision, consistency, and adaptability
- Structuring context hierarchies and variable injection
- Evaluating prompt outputs and refining iterations
Building and Managing Prompt Templates
- Creating reusable prompt templates for teams
- 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 synchronization for dynamic data
Fine-Tuning Models for Domain-Specific Code Generation
- Identifying use cases for fine-tuned models
- Collecting and curating fine-tuning datasets
- 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
Security, Governance, and Performance Optimization
- Ensuring secure handling of AI-generated code
- Establishing policy guards and compliance filters
- Optimizing 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
Krav
- Strong understanding of programming and software architecture
- Experience with AI-assisted coding tools and APIs
- Knowledge of machine learning or prompt engineering concepts
Audience
- AI engineers designing custom AI workflows
- Tooling and platform engineers building internal developer tools
- Senior developers integrating domain-specific AI models
14 timmar
