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MCP Beyond the Chat Window: Build Diagnostics in CI
A practical tour of the Model Context Protocol tools for .NET build diagnostics - the full Binlog MCP toolset, how those tools run inside a GitHub Actions workflow, and what the evaluation data says about the efficiency gains. The post MCP Beyond the Chat Window: Build Diagnostics in CI appeared first on .NET Blog.
.NET 8 and .NET 9 will reach End of Support on November 10, 2026
.NET 8 and .NET 9 will both reach end of support on November 10, 2026. Learn what this means and how to upgrade to .NET 10 (LTS). The post .NET 8 and .NET 9 will reach End of Support on November 10, 2026 appeared first on .NET Blog.
SkiaSharp 4.0 is here: announcing the first stable release
SkiaSharp 4.148.0 is the first stable release of SkiaSharp v4. Learn what is new, why you should be excited, and join the SkiaSharp live event on June 30. The post SkiaSharp 4.0 is here: announcing the first stable release appeared first on .NET Blog.
🚀 I Cracked the YouTube Shorts Formula
🚀 I Cracked the YouTube Shorts Formula (For DevOps Content) A few days ago, I posted a simple DevOps short. No fancy editing. No viral trend. No clickbait. Just a technical observation that engineers could instantly relate to. The Result 👇 📈 4.5K views in under 4 hours ❤️ 2.1K likes 🔥 98.7% average percentage viewed 🏆 Ranked #1 out of my last 10 videos For a niche DevOps creator, these numbers were a pleasant surprise. What Was the Video? The short was based on a simple concept: A relatable
Streaming LLM Tokens to the Browser: The Production SSE Setup
A spinner is a lie. It tells the user something is happening without telling them what. When spectr-ai generates a security report, the LLM produces text token by token over 15 to 40 seconds. If I wait for the full response and then drop it on the page, the user stares at nothing the whole time. If I stream each token as it arrives, the report writes itself in front of them, exactly like ChatGPT. Same wait, completely different feel. A while back I covered SSE for progress bars: the server sends
Building AgentGuardian: A Local-First Security Scanner for Agentic AI Workflows
AI agents are quickly moving from simple chat interfaces to systems that can use tools, access data, trigger workflows, write messages, and sometimes take actions on behalf of users. That shift is exciting, but it also creates a serious security question: How do we evaluate the risk of an AI agent before we deploy it? That question led me to build AgentGuardian, a local-first AI security web app that scans agentic AI workflows for risks such as prompt injection, tool misuse, excessive autonomy,