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https://www.linkedin.com/pulse/beyond-react-how-engineer-new-types-ai-agents-rakesh-aggarwal-ormgf š§šµš¶š š®šæšš¶š°š¹š² š¶š»š°š¹šš±š²š: ⢠Most teams treat agents as prompt tricks ā but real production AI requires system design: ššš®šš² šŗš¼š±š²š¹š¶š»š“, š±š²šš²šæšŗš¶š»š¶ššš¶š° šæš¼ššš¶š»š“, šš®š¹š¶š±š®šš¶š¼š» š¹š®šš²šæš, š®š»š± š²š š²š°ššš¶š¼š» š“šæš®š½šµš. ⢠LangChain defines agents by prompt strategy, while LangGraph defines them by execution topology ā ššµš² ššµš¶š³š š³šæš¼šŗ š°šµš®ššÆš¼š ššµš¶š»šøš¶š»š“ šš¼ š®šæš°šµš¶šš²š°šš¶š»š“ š±š¶šššæš¶šÆššš²š± šæš²š®šš¼š»š¶š»š“ ššššš²šŗš. #AI #GenerativeAI #AIAgents #AgentArchitecture #LangChain #LangGraph #OpenAI #LLM #MultiAgentSystems #AIEngineering #SoftwareArchitecture #EnterpriseAI #MachineLearning #AIInnovation #TechLeadership