Inlined — Akade's Blog

artisanal ramblings about code, written by a human

About

Hi, I’m Alex, a software engineer from Switzerland. I work full-time as an IT Architect / Senior Engineer in a consulting firm but have been into computers since childhood. With more than a decade of experience now, I have worked on various topics from mobile games, frontend, distributed systems, ML, algorithms, LLMs and more. I enjoy everything .NET. But besides .NET, I do love to dabble from time to time in other languages and ecosystems. Concepts transcend and inspiration doesn’t stop at language boundaries.

Opinions and views expressed on this blog are my own and are not influenced by neither my employer nor my clients. The posts are written by myselft, no LLM-generated texts are used unless explicitly stated otherwise.

Talks

  • Beyond the hype – running a business-critical LLM workflow in production, company presentation, 2026
  • Curious Code and where to find it, .NET Day Switzerland, 2024
  • The Infamous Microservice Project, company conference, 2024
  • LLMs & RAG, semi-public company conference, 2024
  • Bringing the Power of Deep Learning to .NET with ONNX and ML.NET, .NET Day Switzerland, 2023
  • C# Source Analyzer & Generators, company conference, 2023
  • Content Based Image Retrieval: Minifigures Edition, semi-public company conference, 2023
  • Let’s build a form scanner with notebooks and OpenCV, .NET Day Switzerland, 2022
  • Let’s hunt Heisenbugs with Microsoft Coyote, company conference, 2022
  • Continuous Benchmarking with BenchmarkDotNet, company conference, 2022
  • Weight watching bees, kickstart labeling using unsupervised anomaly detection, SDS, 2022
  • ML.NET: Machine Learning mit ML.NET, company conference, 2021

Teaching

  • Advanced C#: Modern .NET and .NET 11, 2026
  • Advanced C#: Memory Management, 2024, 2025
  • Performance Workshop, 2023
  • Azure Open AI / RAG, 2023
  • C# Profiling & Benchmarking Dojo, 2022
  • Clean Code with C#/.NET, 2021, 2022, 2023

Open Source

  • Akade.IndexedSet A convenient data structure supporting efficient in-memory indexing and querying, including range queries, fuzzy string matching and approximate vector search.
  • Akade.SnippetLink A streamlined, extensible and opinionated dotnet tool for importing snippets into Markdown files.