Show HN: TDAD – Free n8n style TDD canvas for Cursor/VS Code with runtime traces (github.com)

TDAD (Test-Driven AI Development) has launched a free visual workflow engine that transforms AI coding from a chaotic process into a structured development approach. This tool establishes a disciplined "Plan → Spec → Test → Fix" cycle, ensuring that runtime feedback guides the AI in delivering functional software rather than incomplete code snippets. With key features including local-first operation, compatibility with existing AI models (like ChatGPT and Claude), and zero reliance on external APIs, TDAD promises to mitigate prevalent issues in AI development such as linearity, vague prompts, irrelevant code generation, and ineffective debugging. TDAD's significant innovations include its visual project management (the Canvas) that organizes development tasks into a flowchart format, allowing developers to track which features are complete and which ones need fixing. The platform also introduces auto-generated specifications and tests before coding begins, ensuring a clearer understanding of tasks and demands. Notably, TDAD's unique "Golden Packet" captures detailed runtime trace data when tests fail, providing comprehensive context for efficient code fixes. This toolkit shifts the paradigm of AI-assisted coding from guesswork to precision, ultimately enhancing productivity while maintaining engineering discipline.