AI 요약관련 정보

🔍 Try the AI Fact-Checker I built for this video: ChatGPT Version: https://chatgpt.com/g/g-68fa9f99ed288... Web App: https://check.brainqub3.com/ Consultancy queries: https://brainqub3.com/ Building AI Agents can be challenging, but establishing the right development tools and approaches can significantly ease the process. In this video, I demonstrate my development methodology that has led to the successful creation of Jar3d, a versatile agent capable of orchestrating a team of smaller tool-using agents to achieve a goal. I'll show you how utilising LangSmith for observability aids in debugging, whilst implementing structured outputs enhances the integrity of your agent systems. Additionally, you'll learn how meta prompting enables agents to be flexible and autonomously determine how to collaborate in problem-solving. Jar3d is built atop LangGraph, which integrates seamlessly with LangSmith. This powerful combination of AI Agents, LangGraph, LangSmith, and structured outputs forms the cornerstone of an efficient and effective development approach for creating sophisticated AI systems. Want to enquire about consultancy? Let's chat: https://calendly.com/john-brainqub3/3... Support the development of Jar3d: https://github.com/sponsors/brainqub3 Hands-on project (build a basic RAG app): https://www.educative.io/projects/bui... GitHub repo for Jar3d: https://github.com/brainqub3/meta_expert Chapters Building AI Agents is Hard: 00:00 Meta Prompting: 10:13 Adding new Agents: 18:05 Structured Outputs: 25:44 Setup: 30:02 Demonstrating Observability (LangSmith): 33:55 Additional Considerations: 56:00