<antirez>
5 hours ago
- Traditional open source software follows a fixed development cycle with stable and unstable branches, where bugs are fixed before a release.
- AI coding changes both software development and usage, as users can now ask AI to modify software directly.
- Code repositories should serve as templates or examples for solving problems, allowing users to adapt code for specific needs.
- Unstable or unproven code can be valuable for certain users, like those needing memory-saving features in Redis.
- Projects like DwarfStar show that code bases can guide AI agents to implement features automatically for new models or hardware.
- Multiple experimental branches are now an integral part of projects, enabling community testing and refinement before merging.
- Documentation must be not only human-readable but also understandable by coding agents to facilitate software modification.