Exploring autonomous AI systems and multi-agent architectures
AI Agents represent the next evolution of AI systems—moving from single-turn interactions to autonomous entities that can plan, reason, use tools, and accomplish complex goals over extended periods.
Reasoning + Acting: Interleave thought and action for complex tasks
Create high-level plans then execute step-by-step
Multiple specialized agents collaborating on complex problems
Self-directed agents with long-term memory and goal persistence
Agents interact with external systems through well-defined tool interfaces
Short-term (conversation), long-term (vector DB), and episodic memory
Chain-of-thought, tree-of-thought, and graph-based reasoning
Protocols for multi-agent coordination and task delegation
Composable agent framework
Stateful multi-agent workflows
Autonomous GPT-4 experiments
Multi-agent orchestration
Multi-agent meta programming
Lightweight multi-agent framework
AI agents that write, test, and debug code autonomously
Agents that search, synthesize, and analyze information
Automated support with context awareness and tool access
Agents that query databases and generate insights