@DanKornas: Most agent systems can do impressive work for one session. The hard part is making them remember, reflect, and improve …

Most agent systems can do impressive work for one session. The hard part is making them remember, reflect, and improve over months. GENesis-AGI is an open-source cognitive architecture for builders experimenting with long-running personal AI systems. It helps you study and run a fuller agent stack by combining Claude Code with layered memory, self-learning, earned autonomy, observability, and real-world channels like Telegram, email, browser automation, and task execution. Key features: • 4-layer memory – essential context, proactive recall, deep search, and external knowledge ingestion • Autonomous cognitive cycle – awareness loop, reflection engine, self-learning loop, and ego layer • Earned autonomy – action authority progresses by category and demotes after failures • Resilience infrastructure – Guardian and Sentinel monitor each other with degradation handling • Contributor docs – architecture deep-dives, case studies, journey notes, and setup guidance It’s open-source (MIT license). Link in the reply