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CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment,...

Ditto is a simple self-building coding agent that generates multi-file Flask applications from natural language descriptions. Users describe the app they want, and the system attempts to plan and create routes, templates, static assets, and supporting files. It uses an LLM loop with basic tools to automate part of the coding process. The project is intentionally lightweight and experimental, making it easier to understand than larger agentic coding platforms. Its modular structure separates...