Tag
This article discusses how to manage code quality when using AI coding agents by adopting strategies like spec-driven development and test-driven development to reduce bugs and increase productivity.
Sandy Metz discusses making code small and using tests to guide refactoring, illustrated through the Gilded Rose kata.
Repo0 is a framework for zero-to-all code generation that uses a Dual-DAG architectural state and modularity-guided structural evolution to generate complete software repositories from natural-language requirements, achieving significant improvements in functionality coverage and pass rate compared to baselines.
This position paper argues for shifting from reactive AI flywheel maintenance (patching errors as they occur) to a proactive test-driven approach that maps feedback to a test space of task conditions, showing mathematically that the proactive method achieves better long-term scaling with fewer iterations.
The author shares a TDD skill for AI agents to improve test writing, based on Kent Beck's Canon TDD, and provides a GitHub link.
Argues that pull requests are inefficient for trusted teams and proposes T*D (Test-Driven Development, Trunk-Based Development, Team-focused Development) as an alternative, citing research and industry data.
TDDev automates test-driven development for web application generation by integrating requirement analysis, browser-based validation, and structured repair, improving code quality by 34-48 percentage points over baselines and reducing human intervention to zero.
Maggy v5.0 is an open-source CLI framework that enhances Claude Code into an autonomous engineering platform with multi-agent orchestration, TDD loops, and built-in security protocols. It enables structured workflows through containerized agent teams, cross-machine sync, and automated quality gates.