I gave my AI agent a sleep cycle – it dreams about its errors and fixes them (github.com)

OpenAmer has unveiled an innovative self-improving AI agent that introduces a sleep cycle for its operational learning, enabling it to analyze and rectify its errors autonomously. This agent is a robust, independently developed variant of the Agent architecture from MIT, emphasizing not only verifiability but also a continuous learning loop. Significantly, OpenAmer sets itself apart with features like self-healing UI automation, allowing it to adapt to changes, such as website redesigns, without user intervention—a capability that traditional automation solutions struggle with. The technical implications of OpenAmer are profound; it operates as a living system employing evolutionary principles where skills evolve and improve through user interactions. It boasts unique features such as an A2A agent swarm for peer knowledge sharing, a visual agent builder, and a superintelligence dashboard that provides instant system health scores. With these advancements, OpenAmer promises not just enhanced capabilities but also a more user-centered AI experience that learns and adapts in real-time, challenging the current paradigms in AI agent frameworks.