Agent Patterns

Skill Profile

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• DevOps
• Backend
• Frontend
• AI-RAG
• Security Critical

Overview

AI agents are autonomous systems that use Large Language Models (LLMs) to reason, plan, and execute tasks. Unlike simple chatbots, agents can break down complex problems into steps, use tools to interact with external systems, and adapt their behavior based on feedback. This skill covers agent architectures (ReAct, Plan-and-Execute, Tree of Thoughts, Reflexion), core components (memory, planning, tool use), frameworks (LangChain, AutoGPT, CrewAI, Semantic Kernel), tool design, multi-agent systems, error recovery, guardrails, evaluation, and production deployment.

Why This Matters

AI agents represent a paradigm shift from passive LLM interactions to autonomous problem-solving systems. They enable:

• Complex Task Decomposition: Breaking down user goals into actionable steps
• Tool Integration: Seamlessly connecting LLMs to external APIs and databases
• Adaptive Behavior: Learning from feedback and adjusting strategies
• Multi-Agent Collaboration: Specialized agents working together on complex problems