From Data to Agent: The Complete Open-Source AI Engine

In this episode of the Convo AI podcast, host Derek Zheng has an in-person conversation in Japan with Yongle Yang, Solution Architect at Dify, to explore how their LLM Ops platform is streamlining AI application development through an intuitive workflow canvas and multi-agent orchestration. Yang details Dify’s "do it for yourself" philosophy, Yang challenges developers to build AI that can "replace" their own roles, freeing them to pursue more creative professional side hustles. Key Topics Covered • Dify abstracts LLM Ops complexity into a visual workflow canvas • The "Do It For Yourself" philosophy democratizes AI development • Multi-agent orchestration increases reliability over single agents • Japan accounts for half of Dify’s 500,000 users • Upcoming "one-sentence-to-app" IDE generates workflows from natural language • Developers should build AI that "replaces" their daily tasks Chapters 0:00 Teaser 0:35 Meet Yongle Yang (Dify Background & Story) 2:18 What is Dify & LLMOps Explained 4:43 Why Developers Use Dify (Architecture & Features) 9:06 Agent Design: Single vs Multi-Agent Systems 11:19 Evaluation, Metrics & AI Performance 13:47 Future of AI Apps (One-Sentence-to-App Vision) 16:05 Integrations, Plugins & Real-Time Voice (Agora) 18:31 Human-like AI Conversations & Challenges 20:48 Upcoming Features & Roadmap 21:19 Community Growth & Japan Market 22:55 Key Use Cases (Knowledge Base Focus) 24:03 Developer Advice & Closing Thoughts Resources & Links → Dify: https://dify.ai/ Build Production-Ready Agentic Workflow → Convo AI Newsletter: https://podcast.convoai.world/ Subscribe to stay updated on conversational AI trends → Agora Conversational AI Engine: https://www.agora.io/en/products/conversational-ai-engine/ The industry's most powerful and flexible platform for building conversational AI.