Hook/Intro:

What happens when .NET 10 meets OpenAI? You get a blazing-fast, smart, enterprise-grade web app—built over a weekend! In this post, I’ll show how I fused the latest .NET 10 features with ChatGPT/Azure OpenAI to create a responsive AI assistant in a real-world business app.

Why This Topic Works:

• Combines the hype of AI with the stable release of .NET 10
• Shows real use case → "weekend build" makes it accessible and engaging
• Blends practical code, dev experience, and cool tech — a winning formula

What I Built:

• A lightweight internal tool that allows users to:
• Ask natural-language queries about enterprise data
• Generate business reports using OpenAI GPT
• Summarize customer feedback from SQL data
• Draft internal documents and emails from structured input

Tech Stack:

• .NET 10 Web API
• ASP.NET Core Blazor (for UI)
• Azure OpenAI GPT-4
• Entity Framework Core
• Serilog + Seq for logging
• Redis for caching prompts

Features Used from .NET 10:

• Minimal APIs v2 → rapid endpoint setup
• JIT Compiler Boosts → snappy performance under load
• Span enhancements → optimized string handling for GPT responses
• C# 14 Field-Backed Properties → cleaner data models
• System.Text.Json improvements → faster prompt & response serialization

ChatGPT Integration:

var response = await openAiClient.GetChatCompletionAsync(
    new ChatCompletionRequest
    {
        Model = "gpt-4",
        Messages = new List<ChatMessage>
        {
            new ChatMessage("user", "Summarize customer reviews from last week"),
        }
    });

Tip: Always cache frequent prompts with a smart key (e.g., user + time + intent).

What I Learned:

• Prompt engineering is half the battle.
• ASP.NET Core is incredibly fast for AI-backed endpoints.
• .NET 10’s performance gains are visible when batching API requests.
• Clean architecture + AI = readable, testable, maintainable.

Ready to Try?

Want the GitHub repo, tutorial series, or free starter template? Drop a comment!