The fine line between mistake and innovation in LLMs
Large language models are probabilistic systems. While they're improving rapidly, they can still fail at basic tasks or hallucinate answers - sometimes without us even noticing. In this post, I explore why that happens, how we can mitigate it, and why these mistakes are fundamentally exciting.
Yet another connection reset
Envoy and Kestrel: not exactly love at first sight
Automating my gym bookings with a serverless assistant
My journey to building a serverless assistant that could help me booking my gym classes
Asynchronous programming in .NET
A few personal notes on writing concurrent apps in .NET
Elevate your Prometheus alerts with the help of unit tests
Get the best out of your Prometheus alerts with unit tests
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