ai
OpenAI for .NET Developers Articles, Tutorials & News
OpenAI for .NET Developers articles, tutorials, and news from the DotNetNews archive.
665 articles Updated Page 13 of 27
Browse additional OpenAI for .NET Developers articles from the DotNetNews archive.
OpenAI for .NET Developers articles
Page 13 of 27
Newest first
-
Building AI-Powered Knowledge Extraction Pipelines with ASP.NET Core
C# Corner Issue #480
Unlock insights from unstructured data with ASP.NET Core AI knowledge extraction pipelines. Transform documents into actionable knowledge.
-
Building AI-Enhanced Engineering Metrics Dashboards with Blazor
C# Corner Issue #480
Build AI-enhanced engineering metrics dashboards with Blazor & .NET. Gain predictive insights, detect anomalies, and improve software delivery.
-
From Local to Azure: Deploy Your MCP Server to Production
Medium Issue #480
One codebase. Real Azure data. One deployment target that actually makes sense. Continue reading on Microsoft Azure in Practice »
-
Migrating Agentic Code Python -> C# Part 4
YapCast – Jesse Liberty Issue #480
In the previous blog post we looked at the Blogger (orchestrator) code in C#. Let’s move on to some of the other agents. The Blogger invokes the Researcher, so let’s go there next. The Researcher clas...
-
Improve your AI coding agent with runtime context from Aspire MCP
Tim Deschryver Issue #479
The power of giving an AI agent access to OpenTelemetry data through Aspire MCP is simple: it gives the agent better input to analyze. Instead of reasoning only from source code, the agent can inspect...
-
What's one mistake devs make when building cost-efficient AI apps?
YouTube Issue #479
Most devs over‑optimize the model 🤖 The real leverage is in the system 🔧 Tweaking prompts & swapping models ≠ better outcomes Giving AI the right data + context = better reasoning + results Build th...
-
Spec-Driven Development: A Spec-First Approach to AI-Native Engineering
Microsoft Developer Issue #479
AI has made software delivery faster, but speed alone does not guarantee better outcomes. As teams adopt AI-native development, the real challenge is keeping requirements, design, implementation, and ...
-
From RAG to Agentic RAG: Building Self-Improving AI Applications in .NET
C# Corner Issue #479
Learn how Agentic RAG extends traditional Retrieval-Augmented Generation by combining AI agents, reasoning, planning, and tool usage to build intelligent self-improving AI applications in .NET.
-
Building Context-Aware Enterprise Search Applications with ASP.NET Core
C# Corner Issue #479
Build intelligent, context-aware enterprise search with ASP.NET Core, vector databases, and AI for enhanced productivity and knowledge discovery.
-
Context Engineering for AI Applications: Beyond Prompt Engineering
C# Corner Issue #479
Learn how context engineering goes beyond prompt engineering by optimizing retrieval, memory, tool outputs, and information pipelines for enterprise AI applications in .NET.
-
We built an AI tool for .NET/C# developers in 2 days
Round The Code Issue #479
We built an AI tool for .NET and C# developers in just 2 days using Claude's API. Here's how we did it, the prompts we used, and how you can try it now. The page We built an AI tool for .NET/C# develo...
-
Structured Outputs in LLM Applications: A Complete C# Developer Guide
C# Corner Issue #479
Learn how to implement structured outputs in C# AI applications. Discover schema validation, strongly typed models, JSON responses, and best practices for building reliable enterprise LLM solutions.
-
How to Build Offline AI Applications in .NET Without Cloud Dependencies
C# Corner Issue #478
Build offline AI apps in .NET without cloud. Leverage local models like Phi & tools like Ollama for privacy, cost savings, and faster responses.
-
Building AI-Powered Apps with Claude and ASP.NET Core
C# Corner Issue #478
Integrate Claude AI into ASP.NET Core with C# to build intelligent apps. Learn API setup, service creation, and REST endpoint exposure.
-
Creating a Simple MCP Server in .NET
The Long Walk — RSS Issue #477
In my previous post, I covered how to interact with a local LLM from .NET using LM Studio. In this post, I’m going to take that a little…
-
On .NET Live - Demystifying Microsoft Agent Framework Middleware
YouTube Issue #477
In this session we'll walk through how Daniel Costea uses ChatClient and Agent middleware to turn plain .NET AI agents into production‑ready systems with observability, safety, and cost control. Start...
-
Implementing AI Memory Systems in C# Using Vector Databases
C# Corner Issue #477
Learn how to implement AI memory systems in C# using vector databases. Discover embeddings, semantic search, memory architectures, and best practices for building intelligent AI applications.
-
CLAUDE.md for .NET Developers - Complete Guide with Templates
codewithmukesh Issue #476
Write the perfect CLAUDE.md for .NET projects: memory hierarchy, auto memory, AGENTS.md interop, and copy-paste templates. Updated for mid-2026.
-
20 Advanced Claude Code Tips for .NET Developers
codewithmukesh Issue #476
Twenty advanced Claude Code tips for .NET developers: context engineering, hooks, subagents, MCP, worktrees, and model selection to ship faster in 2026.
-
-
The Invisible Engine Behind AI Agents: Why Process Management in .NET
Medium Issue #475
Most developers don’t wake up thinking about process management.
-
Building AI-Native APIs with ASP.NET Core and Natural Language Interfaces
C# Corner Issue #475
Build AI-native APIs with ASP.NET Core. Leverage natural language, intent processing, and semantic search for intelligent applications.
-
Feature Flags for AI Applications: Safe Deployment Strategies in .NET
C# Corner Issue #475
Safely deploy AI in .NET with feature flags. Control rollouts, A/B test models, manage costs, and ensure governance for AI innovations.
-
Building AI Agents in .NET with Microsoft Agent Framework
Medium Issue #475
A practical walkthrough of MAF’s core primitives — agent sessions, streaming, and SignalR integration — built around a real working…
-
How to Use Semantic Kernel for AI Application Development
C# Corner Issue #473
Learn how to use Semantic Kernel for AI application development in .NET. Build chatbots, AI assistants, RAG applications, and intelligent workflows.