How to Use Agentic AI: LLMs, AI Agents & Prompt Engineering in Action
The content discusses transitioning from using a single large language model (LLM) to an agentic workflow for solving a problem involving validating explanations for missing items in an order, highlighting the limitations of single LLM prompts and the benefits of a multi-step approach.
MAIN POINTS FROM TRANSCRIPT
- Initial attempts with increasingly larger LLMs failed to solve the problem.
- The problem involved verifying explanations for missing order items.
- An agentic workflow was adopted, using multiple prompts to handle tasks.
- The workflow included extracting items, validating reasons, and comparing outputs.
TAKEAWAYS
- Single LLM prompts may not suffice for complex problems.
- Agentic workflows can effectively handle tasks with multiple steps.
- Validating explanations requires more than just identifying them.
- Multi-step processes can address edge cases better than single prompts.