Building Agentic AI Workflows and Multi-Step Pipelines with C# and Semantic Kernel

Introduction

Integrating AI agents into existing platform ecosystems requires a disciplined approach to async task execution, prompt orchestration, and state persistence.

In this guide, I share engineering lessons from building autonomous agents using **C#**, **ASP.NET Core**, and **Semantic Kernel**.

Core Architecture Principles

1. **Decoupled Reasoning**: Keep LLM prompts abstracted from HTTP transport handlers. 2. **Persistent Agent Memory**: Store execution state and telemetry in MongoDB. 3. **Resilient Error Handling**: Use retry logic and strict timeout bounds on external AI endpoints.