razzant/ouroboros

Ouroboros addresses the fragmentation of AI agents by providing a single agent with a continuous identity and memory that persists across sessions, unlike stateless or task-specific agents. It also enables self-modification and autonomous evolution, allowing the agent to improve its own implementation without human intervention, which is not typically offered by other frameworks.

Developers can build autonomous agents that manage long-term projects, maintain context and memory over extended periods, and coordinate complex multi-agent workflows. Real-world use cases include automated software development, continuous research and analysis, personal AI assistants with persistent memory, and self-improving automation pipelines. The ceiling is high: the agent can theoretically evolve its own capabilities, integrate new tools, and adapt to new domains without manual reprogramming.