AI Agentic Framework
An architectural paradigm where AI systems autonomously perceive, reason, and act to achieve complex goals without continuous human intervention. Key components include planning, memory, tool use, and execution loops.
Core Concepts
- Autonomy: The ability to operate independently within defined constraints.
- Tool Use: Integration with external APIs, code interpreters, or databases to perform actions.
- Memory: Short-term context management and long-term knowledge retrieval.
- Planning: Breaking down high-level goals into executable steps.
Notable Implementations
- hermes-agent: An open-source agentic framework by Nous Research.
- Focuses on transparency and open-weight models.
- Supports various LLM backends for flexibility.
Recent Developments
- Hermes Agent /loop Feature:
- Introduced automated recurring task capabilities.
- Allows agents to execute tasks on a scheduled basis without manual triggering.
- Demonstrated with Qwen3.8 27B model for efficient loop management.
- See loop Feature: Automated Recurring Task Demo for hands-on details.