Back in 1985, computer scientist Peter Naur wrote “Programming as Theory Building”. According to Naur — and I agree with him — the core output of software engineers is not the program itself, but the theory of how the program works. In other words, the knowledge inside the engineer’s mind is the primary artifact of engineering work, and the actual software is merely a by-product of that.
Programming as Theory Building - Peter Naur
Programming as Theory Building - Peter Naur · GitHub
Programming as Theory Building: Why Senior Developers Are More Valuable Than Ever
Peter Naur's 1985 theory of programming explains why experience matters more in the age of AI-generated code
Software Design is Knowledge Building
The product of software development is not code but a mental model, a theory: a specific way of explaining the world.
Why Software Engineering Is Indispensable in the Age of Coding Agents
Can AI make Software Engineering (SE) -- the discipline -- obsolete? And can it make software engineers -- the professionals -- redundant? This paper argues that the rise of capable AI coding...
The third golden age of software engineering – thanks to AI, with Grady Booch
The third golden age of software engineering – thanks to AI, with Grady Booch
The Gap Through Which We Praise the Machine
My current theory of agentic programming: people are amazing at adapting the tools they're given and totally underestimate the extent to which they do it, and the amount of skill we build doing that is an incidental consequence of how badly the tools are designed.
Agentic Engineering Management
To what extent AI is OK to use in software development might be debated, but in general, the idea is not a controversial one anymore. The debate rather moved on from code completion and simple PR summarizations to Agentic Engineering, where an execution loop allows an AI Agent to function
Agents
Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as “the study and design of rational agents.”
Running an AI-native engineering org | Claude
How the Claude Code engineering team’s processes and structure changed once agentic coding became the default way of working.
Why AI hasn’t replaced software engineers, and won’t
Coding agents as normal technology
AI should help us produce better code - Agentic Engineering Patterns
AI should help us produce better code - Agentic Engineering Patterns
AI made me doubt everything about programming by Felienne Hermans - DDD Europe 2026
AI made me doubt everything about programming by Felienne Hermans - DDD Europe 2026
How Cursor is building the future of AI coding with Claude
The Eternal Sloptember
I’m calling it now, the adoption of AI agents into software development will be one of the most costly mistakes in the field’s history. Agents cannot program, and it’s taking longer and longer to realize that they can’t. They are a highly sophisticated statistical model designed to mimic the distribution of programming. The output is broken, but in a way that’s getting harder and harder to detect. Which is exactly what you’d expect from an increasingly accurate statistical model.