This blog is an endeavour into exploring the Epistemology of AI systems. It applies second-order cybernetics to contemporary questions in AI development and deployment, examining how human observers and AI systems are always already entangled in recursive relationships that shape what we can know about artificial intelligence. Drawing inspiration from thoughtful practitioners like Hamel Husain, Eugene Yan, Jason Liu et al., these posts explore the epistemological dimensions of Human-AI interaction that resist purely technical analysis. Every claim about AI capabilities emerges from human observation conducted through language and conceptual frameworks, meaning we never encounter „pure“ AI systems but always Human-AI systems where the observer participates in constructing what is observed. Rather than providing definitive answers about what AI systems „really“ are, the blog posts develop frameworks for asking different questions about knowledge construction, meaning-making, the recursive dynamics between artificial and human intelligence, and cybern-ethics. The goal is to expand the space of productive inquiry for practitioners seeking inspiration from a theoretical approach to AI development, honoring both the genuine novelty of artificial intelligence and the irreducible role of human observation in making sense of that novelty. Readers will find no solutions here, but rather invitations to think „out-of-the-box“ about the strange new forms of technology in our times.
Explore by Category
Maths
Mathematical foundations and formal approaches to understanding AI. From information theory to the calculus of indication.
AI Engineering Concepts
Technical concepts explained through theoretical lenses. Architecture patterns, training dynamics, and the emergence of intelligence.
Human-AI Systems
The dynamics of human-AI collaboration and interaction. Distributed cognition, trust, and the co-evolution of humans and machines.
Legends
Theoretical insights from the giants who shaped our understanding. From Ada Lovelace to Heinz von Foerster and beyond.
Cybern-ethics
Ethical questions through the lens of cybernetics and systems theory. Responsibility, autonomy, and moral agency in distributed systems.
The rapid development of generative AI has created an unprecedented situation whose broader implications unfold in real-time, often outpacing our ability to comprehend their significance.This dynamic has sparked important conversations among thoughtful AI practitioners and researchers. Hamel Husain’s work on AI evaluation methodologies and his insights into the gap between technical metrics and real-world AI product development, and similar investigations by experts grappling with the gap between technical implementation and real-world impact point toward a crucial need: developing adequate theoretical frameworks for understanding what we’re building and how it relates to human experience.
I recently switched to Cursor, a new AI-enhanced code editor that's been getting a lot of attention lately. While it's been a great experience so far, there was one small hiccup on macOS with .code-workspace files. Here's how I solved it.
If you're tired of slow package installations and complex dependency management in Python, uv might be exactly what you need. Written in Rust, uv is a blazing-fast package manager that aims to replace pip, pip-tools, pipx, poetry, and more. Let's dive into why it's awesome and how to get started.