Using Agentic AI to create smarter solutions with multiple LLMs (step-by-step process)

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AI Summary

Overview

• The video discusses the concept of Agentic AI, predicted to be a prominent topic in 2025.

Key Points

1. Definition of Agentic AI
   • Explored as a concept integrating multiple AI models to improve tasks.
   • Compared to traditional LLM interactions, which lack reflection and editing.
2. Writing with Compound LLMs
   • Using multiple LLMs can enhance output quality by allowing critique and revision.
   • Example process:
     • Draft a marketing plan with the first LLM.
     • Critique the draft using a second LLM.
     • Revise the plan based on feedback with a third LLM.
3. Three Mental Leaps in Understanding
   • Mental Leap 1: Refer to LLMs as agents responsible for distinct tasks (drafting, critiquing, revising).
   • Mental Leap 2: Acknowledge that not all agents are LLMs; some may be tools (e.g., Google search).
   • Mental Leap 3: Consider the workflow of agents as dynamic, allowing flexible paths rather than a predetermined sequence.
4. Integration of Agents and Tools
   • Agents can perform tasks outside traditional LLM capabilities, such as gathering data.
   • Orchestrator agents can manage workflows based on specific needs and conditions.

Conclusion

• The video aims to inform viewers about emerging AI trends and encourage exploration of practical applications in organizational contexts.