Simple non-hype agentic coding workflow for well-established codebases (alyosha.net)

A developer has introduced a streamlined coding workflow utilizing agentic tools like Codex CLI to enhance productivity when working on established codebases. This approach, tested on a medium-sized project with robust test coverage, moves away from traditional inline suggestions and chat, opting instead for a structured process that incorporates markdown documentation for ticket tracking, research, and planning. Each ticket is complemented by a research document and a detailed implementation plan, enabling a clear feedback loop that promotes efficient coding. This workflow is significant for the AI/ML community as it demonstrates the practical utility of agentic coding in real-world development environments. By integrating AI agents into everyday tasks, such as code compilation and testing, developers can optimize their efficiency while maintaining code quality. The meticulous organization of files and the emphasis on feedback loops not only help in simplifying complex tasks but also highlight how AI tools can adapt to well-defined software projects, potentially paving the way for more sophisticated AI-assisted development practices in the future.