In this article, Carson Gross discusses an alternative approach to software development that challenges the principles outlined in 'Clean Code.' Carson advocates for allowing larger functions in certain cases, preferring integration tests over unit tests, and minimizing the number of classes and interfaces. He shares examples from successful software projects that demonstrate these practices can lead to maintainable, high-quality code.
Does Code Cleanliness Affect Coding Agents? A Controlled Minimal-Pair Study
As autonomous coding agents see rapid adoption, their evaluation has primarily focused on task completion rates holding the target codebase fixed. This leaves a critical question unanswered: does the structural and stylistic quality, or ``cleanliness'' of the underlying code affect an agent's ability to navigate and modify it? To isolate the effect of code cleanliness from agent capability, we introduce an evaluation protocol built around minimal pairs: repositories that match on architecture, dependencies, and external behaviour, but differ on static-analysis rule violations and cognitive complexity. The pairs are constructed in both directions, by agent pipelines that either degrade a clean repository or clean a messy one. We author 33 tasks across six such pairs, evaluated through hidden tests at the application's public surface. Across 660 trials with Claude Code, code cleanliness does not change the agent's pass rate. However, it substantially alters the agent's operational footprint: agents working on cleaner code use 7 to 8% fewer tokens and reduce file revisitations by 34%. Our findings suggest that traditional maintainability principles remain highly relevant in the era of AI-driven development, shaping the computational cost and navigational efficiency of coding agents. Code cleanliness joins model choice, harness, and prompting as a factor that materially affects agent behaviours.
Write code that is easy to delete, not easy to extend.
“Every line of code is written without reason, maintained out of weakness, and deleted by chance” Jean-Paul Sartre’s Programming in ANSI C.
Antithesis: autonomous software testing
Try the Antithesis autonomous testing platform and find bugs in your software with perfect reproducibility
Improving Science That Uses Code
Abstract. As code is now an inextricable part of science it should be supported by competent Software Engineering, analogously to statistical claims being
How to create software quality.
I’ve been reading Steven Sinofsky’s Hardcore Software, and particularly enjoyed this quote from a memo discussed in the Zero Defects chapter: You can improve the quality of your code, and if you do, the rewards for yourself and for Microsoft will be immense. The hardest part is to decide that you want to write perfect code. If I wrote that in an internal memo, I imagine the engineering team would mutiny, but software quality is certainly an interesting topic where I continue to refine my thinking. There are so many software quality playbooks out there, and I increasingly believe that all these playbooks work in their intended context, but are often misapplied.
Testing can be fun, actually
Writing and maintaining tests is boring. But they're also some of the most valuable code we can write. With this blog post you'll learn a criminally underrated testing technique to add to your testing toolbox that can make tests a whole lot more pleasant.
R. S. Doiel, Software Engineer/Analyst — Robert's ramblings
By R. S. Doiel, 2026-02-21 (revised: 2026-03-03, epilogue added 2026-03-27)
Diving into Claude Code's Source Code Leak
Engineer’s Codex is a publication about real-world software engineering.
Modeling Software With Quint - Zicklag's Leaflets
I believe having good abstractions is key to writing good code. But as a coder, I often write code in an effort to find those abstractions…
Code Worth Writing - Ray Myers | SSW 2026
What I Found Interesting in Claude Code's Source
A breakdown of the most interesting engineering patterns in Claude Code's leaked source code: composable system prompts, runtime instruction injection, context compression, forking, prompt caching architecture, and more.
A new era for software testing - <antirez>
SOLID: The Software Design, Architecture & Testing Wiki
Learn to write testable, flexible, maintainable code with TypeScript.
Priivacy-ai/spec-kitty
Spec-Driven Development for serious software developers. Spec Coding with with Claude, Cursor, Gemini, Codex. Kanban dashboard, git worktrees, auto-merge and more.