Agentic frameworks

Agentic frameworks transform Large Language Models (LLMs) into autonomous, goal-driven digital workers capable of multi-step planning and tool use.

These frameworks provide the orchestration layer necessary to build reliable, production-ready AI agents. They enable complex workflows by giving the LLM a 'brain' for dynamic decision-making, memory, and tool integration (e.g., calling APIs, using vector databases). Leading examples like Microsoft AutoGen and CrewAI specialize in multi-agent collaboration, allowing distinct agents with specific roles to converse and delegate tasks to achieve a complex objective. This architecture is key to moving beyond simple chatbots, driving adoption: Gartner predicts 33% of enterprise software will feature agentic AI by 2028.

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