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10 Agentic AI Patterns That Are Reshaping Intelligent Systems
- Agentic AI patterns are design blueprints defining how intelligent agents behave, interact, and plan, resembling personality types for AI.
- Reflective agents review and improve their outputs autonomously, as seen in AI coding assistants like GitHub Copilot.
- Task-oriented agents focus on specific tasks, enhancing automation of business processes like appointment scheduling.
- Hierarchical agents operate within a chain of command, beneficial for orchestrating complex projects with structured control.
- Coordinating agents assign roles in team settings for efficient operations like DevOps pipelines.
- Distributed Agent Ecosystem enables autonomy at scale in decentralized networks, beneficial for IoT applications.
- Human-in-the-Loop Collaboration agents work with humans for critical decisions, enhancing safety in sectors like healthcare.
- Self-learning agents adapt based on feedback, making AI systems more responsive and user-friendly.
- RAG-Based agents retrieve external information for better responses, combining generative models with factual reliability.
- Planning agents build and execute strategies to meet user goals efficiently, suitable for complex workflows.
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