Simon Späti is a data engineer, technical author and educator who publishes the ssp.sh blog, a connected public collection of notes and the developing book Patterns of Data Engineering. He explains data systems alongside the habits used to learn and maintain them.[1][2]
Start with The problem is not AI code, but not knowing about system architecture or intent →
Education
Links
Website About and now CVCareer
Connect working knowledge across formats
Späti’s site traces its history from early web projects to data writing in 2015 and a public second brain in 2022. His blog, notes and book chapters link to one another, letting a reader move from a broad explanation to related concepts. He describes a transition from data engineering into technical writing and launched freelance work in 2024.[2]
Build data systems before teaching their patterns
Späti’s CV describes data engineering at Bedag Solutions, Airbyte and Rohde & Schwarz SwissQual, following data-warehouse work at Satair. His projects span database integration, orchestration and analytical platforms. That implementation background informs writing that connects individual tools with the architecture and operating work around them.[3]
Ideas
His essay on AI-written code argues that system knowledge and design intent can disappear when teams generate changes without understanding them. More code increases the amount that must be maintained. He connects that maintenance burden to architecture, fundamental skills and the ability to explain why a system is built as it is. The essay is an evolving personal argument, not a controlled study of coding productivity.[4]
Tools, writing & talks
Writing, research & talks
Start here
An argument for retaining architectural understanding and design intent in agent-assisted development.
Read the maintenance section and test its questions against a system you know. Familiarity with software projects helps; follow backlinks to explore the underlying architecture and knowledge-management ideas.
Author[4]Original source