Back to All Courses

Intelligent Design Patterns for AI-Driven .NET Systems

Duration: 12 Hours

Difficulty Level: Advanced

Audience: Professionals

Certificate of Completion by Code.Hub

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.

By the end of this module, 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

Introduction to AI Design Patterns

  • Traditional vs AI-driven design patterns
  • Challenges in AI system design
  • Overview of intelligent architectures

AI Practice: Use AI to suggest architecture patterns for a given problem

Prompt & Interaction Patterns

  • Prompt templates and chaining
  • Structured outputs (JSON schemas)
  • Managing context and memory

AI Practice: Design prompts for reliable API responses

 

 

Tool Integration & Function Calling

  • Tool-calling pattern
  • Mapping AI outputs to system actions
  • External API integration

AI Practice: Implement tool invocation flow using AI-generated schemas

 

RAG Pattern in .NET

  • Retrieval-Augmented Generation
  • Vector DB integration
  • Context injection strategies

AI Practice: Build a simple RAG pipeline with AI assistance

Agent & Workflow Patterns

  • Multi-step reasoning
  • Planner/Executor pattern
  • Agent orchestration

AI Practice: Design an agent workflow using AI prompts

 

Validation, Safety & Observability

  • Guardrails and validation layers
  • Handling hallucinations
  • Monitoring AI behavior

AI Practice: Add validation and logging to AI-driven components

Roles:

  • .NET Developer
  • Backend Developer
  • Software Engineer
  • ΑI Engineer

Seniority:

  • Mid
  • Strong experience with C#, ASP.NET Core, and object-oriented design principles
  • Familiarity with basic AI/LLM concepts and API integration

Sessions can be delivered via the following formats:

  • Live Online – Interactive virtual sessions via video conferencing
  • On-Site – At your organization’s premises
  • In-Person – At Code.Hub’s training center
  • Hybrid – A combination of online and in-person sessions

Interested for

Intelligent Design Patterns for AI-Driven .NET Systems
By submitting, you agree with Terms & Conditions