.NET
EF Core 11's vector search announcement was genuinely exciting, if you're on SQL Server. But according to Stack Overflow's 2024 Developer Survey, PostgreSQL is the most-used database among professional developers at 49%. Half of us watched that announcement and thought: "Cool. Doesn'
.NET
The current AI/RAG stack for .NET developers is architecturally absurd. You've got SQL Server holding your domain data, Pinecone or Qdrant sitting in a separate cloud for vectors, a sync pipeline duct-taped between them to keep embeddings consistent, and a completely different SDK with its own query
dotnet
Microsoft finally killed the "which SDK do I use for agents?" problem. If you've been watching the AI agent space from the .NET sidelines, confused by AutoGen's Python-first research vibe, or frustrated that Semantic Kernel felt awkward for multi-agent scenarios, your wait is over.
AI
I've been using GitHub Copilot since the early preview days. Inline suggestions, Chat panel, slash commands — the whole stack inside VS Code. It's a productivity multiplier. But it has always been confined to one editor window, one context, one conversation at a time. The new GitHub
AI
The generic entity pattern I wrote about last time is smart. But smart has a ceiling -- in high-throughput systems and AOT targets, that ceiling is lower than you think. Source generators blow past it. Where the generic pattern starts costing you To be clear: the generic entity service pattern
AI
Every project I join has the same problem. Ten entities, ten controllers, ten services, ten data access classes and all doing the exact same thing. A ProductService that's a copy-paste of CustomerService, which is a copy-paste of OrderService. Nobody questions it. It just grows. I got fed up
AI
I want Gemini in my .NET API without a dependency on whichever SDK is flavour of the month. The official Google .NET SDK targets net8.0/netstandard2.0 and its multimodal API is still in flux. A typed HttpClient, System.Net.Http.Json, and 80 lines of C# gets you
AI
Copilot Without Context Is a Fast Way to Generate Tech Debt Out of the box, Copilot defaults to the patterns it was trained most heavily on: controllers, [ApiController], IActionResult, DbContext calls direct in endpoints. That is Microsoft tutorial code. It is not production architecture. The suggestions are fluent and fast.
AI
The third time Claude Code suggested I scaffold a controller, I stopped typing and started writing a CLAUDE.md file. That's the problem with AI coding assistants without context: they default to whatever Microsoft's documentation says. Ask Claude to add a new entity and it reaches
AI
Every time I paste a snippet into ChatGPT or Claude, I'm sending proprietary code to a third-party server. That's a non-starter for client work. Add the per-token costs once your usage scales, and the internet dependency when you're travelling — or just in a hotel
AI
77.2% on SWE-bench Verified. A 27B open-weight model. That number sat with me for a while when I first saw it, because Claude Opus 4.6 — the current best-in-class closed model for coding — scores 80.8%. We're talking about a 3.6-point gap between a model you