Agentic Engineering: Building Without Writing (dehora.net)

In a groundbreaking development within the AI/ML community, an engineer accomplished the creation of a fully functional personal AI assistant named "Tars" without writing any traditional code. Utilizing a methodology called Agentic Engineering, the project leveraged AI models to describe the assistant's features and functionalities. Tars integrates with various applications like Obsidian and Todoist and supports multiple interfaces, including a command line interface (CLI), web interface, email, and a Telegram bot. Over the course of development, 35 features were implemented with approximately 7,300 lines of Python code generated entirely by AI agents Claude and Codex, which execute tasks from memory management to tool integration. This approach is significant as it exemplifies a shift in software development paradigms, making programming more accessible and efficient through AI-assisted development. Tars employs a sophisticated memory system, enabling it to retain user-specific information across sessions while utilizing a hybrid semantic/keyword search method for efficient querying. By actively incorporating feedback and corrections from users, Tars demonstrates an innovative learning mechanism that could set a new standard for developing personalized AI tools, potentially streamlining workflows and enhancing productivity in various tech-driven domains.