Intelligent Design Patterns for AI-Driven .NET Systems
Description
This course introduces developers to advanced design patterns tailored for building AI-driven systems in the .NET ecosystem. Participants will explore how traditional software design patterns evolve when integrating Generative AI, LLMs, and agent-based workflows. The course covers patterns for prompt orchestration, tool integration, RAG pipelines, and AI-enabled decision systems. It also addresses architectural concerns such as modularity, scalability, and maintainability in AI-native applications. Through hands-on labs, learners will implement intelligent patterns using ASP.NET Core, integrating AI services into clean and extensible architectures. Emphasis is placed on controlling AI behavior, ensuring reliability, and applying best practices in production environments. By the end of the training, participants will be able to design robust, reusable patterns for AI-enhanced .NET systems.
🕒 Duration: 12 hours
👥 Target Audience:
- Roles: .NET Developer, Backend Developer, Software Engineer, ΑI Engineer
- Seniority: Mid-Senior
Webinar Content
|
Module 1: Foundations of AI Design
|
Introduction to AI Design Patterns |
|
| Prompt & Interaction Patterns |
|
|
|
Module 2: Core AI Patterns
|
Tool Integration & Function Calling |
|
| RAG Pattern in .NET |
|
|
| Module 3: Advanced Patterns | Agent & Workflow Patterns |
|
| Module 4: Reliability & Governance | Validation, Safety & Observability |
|
Learning Objectives:
After attending this webinar participants will be able to:
- Apply AI-specific design patterns in .NET applications for scalable and maintainable systems
- Implement prompt orchestration, tool-calling, and RAG patterns effectively
- Design modular architectures for AI-driven workflows and services
- Integrate LLM capabilities into existing systems using structured patterns
- Ensure reliability, validation, and governance in AI-powered applications
Prerequisite Knowledge
- Basic experience with .NET (ASP.NET Core) and SQL Server
- Familiarity with software development workflows (Git, APIs, testing)

