Topics
Every article grouped by what it covers: .NET, C#, Azure, AI agents, databases, architecture.
- AI — Building with AI — agents, LLMs, RAG, prompting, and the engineering behind shipping AI features that hold up.
- API — Designing and building APIs — REST, GraphQL, gRPC, integration patterns, and the contracts that hold systems together.
- .NET — Deep dives into the .NET platform — runtime internals, performance, concurrency, and the corners of the framework worth knowing.
- SDLC — How software actually gets built — planning, process, testing, review, and shipping with (and without) AI in the loop.
- Security
- Database — Data and databases — modeling, querying, vector search, and choosing the right store for the job.
- Tests — Testing and quality — from unit and architecture tests to AI-assisted, automated testing you can trust.
- Azure — Practical Azure — cloud architecture, services, and the trade-offs of building and running real systems on it.
- IoT
- MCP — The Model Context Protocol — how it works, how to build servers and tools, and why it is reshaping AI integrations.
- Cosmos DB — Azure Cosmos DB in practice — data modeling, the Core (SQL) API, partitioning, and globally distributed NoSQL.
- C# — The C# language up close: idioms, patterns, and the features that make everyday code cleaner and faster.