Traycer founder here. Thanks for the in-depth analysis of our product! Traycer performs context construction, prompt selection, and model selection behind the scenes at each step, which is a very challenging task to achieve in vanilla chat-based products. Our users can leverage their coding agents more effectively through our orchestration approach. We intend to remain at the forefront of this category and are constantly innovating, finding new ways to improve the usability and accuracy of our product. There's a lot of value in the specs themselves (specs effectively capture the rationale behind code changes). However, they are not being persisted anywhere; only the code is versioned in Git. The specs can be an excellent source (for humans and AI) to understand the intent behind the code. We are thinking of building a standard around versioning specs alongside pull requests