







Antithesis: autonomous software testing
Try the Antithesis autonomous testing platform and find bugs in your software with perfect reproducibility

Not just development, distribution of software may change as well - <antirez>
The struggles of an open source maintainer - <antirez>
Control the ideas, not the code - <antirez>
GNU and the AI reimplementations - <antirez>
Programmers are not different, they need simple UIs. - <antirez>
How Antithesis Turned exe into a Sandbox for Agentic Software Tests - exe.dev blog
Carl Sverre spends a lot of time thinking about how to give AI agents the right amount of power. Give them too little, and they can’t do real work. Give them too much, and they might blow up your tech stack. As a software engineer at Antithesis, an autonomous software testing platform, that question is core to how Sverre thinks about designing tools in the era of advanced AI.

Coding with LLMs in the summer of 2025 (an update) - <antirez>
Being Linux Torvalds - <antirez>
Don't fall into the anti-AI hype - <antirez>
Hypothesis, Antithesis, synthesis
Introducing Hegel, our new family of property-based testing libraries.

Anti-patterns | Impeccable
37 deterministic detection rules that flag the visible tells of AI-generated interfaces and common quality issues. Used by npx impeccable detect and the browser extension.
Code Worth Writing - Ray Myers | SSW 2026
The Spoofax language workbench | Proceedings of the ACM international conference companion on Object oriented programming systems languages and applications companion
As part of the Digital Library's transition to Open Access, new features for researchers are available in the Premium Edition. Click here to learn more.

</> htmx ~ Codin' Dirty
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.
