← Back to catalog
📚 Series

From Software Engineering to AI Architecture

A sixteen-episode micro-learning course for architects and tech leads who already know software engineering and cloud, and now have to build, operate, govern and pay for AI systems. It runs from why a model breaks ordinary engineering assumptions, through industrialisation, quality attributes and the generative shift, to governance, security and economics — grounded end to end in a fifty-document reference corpus. Each episode pairs a written article with an audio podcast.

Episodes (2)

  1. 1 Ep 1 — Why an AI System Is Not Ordinary Software A statistical model inside a software system breaks assumptions that forty years of software engineering take for granted. Learn to name the three axes along which an AI system changes, diagnose a real system with the hidden-technical-debt vocabulary, and see exactly where classical practice stops being sufficient.
  2. 2 Ep 2 — Data, Model, Code — The Three Pipelines Behind every AI system are three pipelines — for data, for the model, and for deployment — and the way you combine them is an architectural choice, not an accident. Learn to recognise the patterns, pick a serving strategy on purpose, and understand why the serialization format decides how portable your model really is.