AI Agent 初體驗
19:10~ 19:50
- 講者：陳葵懋 / Ian Chen
- Semantic Kernel Developers Taiwan
- 簡介： 微軟 AI 人工智慧最有價值專家（MVP），同時也是微軟認證講師（MCT）。 熟悉 .NET、Azure 、容器化、Azure OpenAI 與生成式AI應用解決方案，曾任微軟 TechDay、Devdays、MWC、MOPCON 等研討會講師。
共同著作：
- LangChain 奇幻旅程：OpenAI x Gemini x 多模態應用開發指南
- 極速 ChatGPT 開發者兵器指南：跨界整合 Prompt Flow、 LangChain 與 Semantic Kernel 框架
- 駕馭 ChatGPT 4: 探索 Azure OpenAI 與 Cognitive Service for Language 開發實踐 （使用 .NET 與 Node.js）
- 議程：AI Agent 初體驗
- 議程簡介： 生成式AI熱潮從文字生成發展至近期開始被討論觀注的AI Agent議題，那什麼是AI Agent，該怎麼做AI Agent，AI Agent與過去的GPTs，外掛Plugins有什麼差異，AI Agent 真的很神嗎 , 透過範例來了解AI Agent的實作過程以及解答上述疑惑
From Executor to Orchestrator: The New Developer Paradigm
Format: Technical talk with live demos, code and prompt examples
Description:
The role of the developer is fundamentally changing. We're moving from being executors who write every line of code to becoming orchestrators who conduct AI agents to build complex systems. This talk, based on my essay about transitioning from traditional coding to AI orchestration, shares practical insights from a year of experimenting with multi-agent development workflows. 🔗 Essay linked here: https://pivotech.substack.com/p/from-executor-to-orchestrator-my
Through real code examples and live demonstrations, I'll walk through my evolution from using ChatGPT for learning CS50 concepts to orchestrating Claude, Gemini CLI, and NotebookLM to build complete products. You'll discover the three distinct schools of AI development I've identified through hands-on experimentation: the One-Shot method, the Incremental approach, and my hybrid Layering technique.
I'll share the workflows I use to go from customer discovery sessions to deployed applications, including the mistakes, frustrations, and breakthroughs that shaped my approach. We'll explore the "Legacy Codebase Problem" that emerges from AI-generated code, the "Hyper-specificity Paradox" of detailed prompting, and the new skill set required to become an effective AI orchestrator.
Key Takeaways:
Three proven patterns for AI-assisted development and when to use each
Practical orchestration workflows for complex projects
The emerging skillset of the developer-orchestrator
How to maintain technical depth while leveraging AI efficiency
Real-world pitfalls and how to navigate them
Target Audience: Developers looking to evolve their practice in the age of intelligent agents. Minimal level of AI development experience required e.g. prompting Claude
Nkechi Anyanwu
Platform Sponsors
Torc is a community-first platform bringing together remote-first software engineer and developer opportunities from across the globe. Join a network that’s all about connection, collaboration, and finding your next big move — together.
Join our community today!
Don't let broken lines of code, busted API calls, and crashes ruin your app. Join the 4M developers and 90K organizations who consider Sentry “not bad” when it comes to application monitoring. Use code “guild” for 3 free months of the team plan.
https://sentry.io
AI Agent 初體驗
19:10~ 19:50
- 講者：陳葵懋 / Ian Chen
- Semantic Kernel Developers Taiwan
- 簡介： 微軟 AI 人工智慧最有價值專家（MVP），同時也是微軟認證講師（MCT）。 熟悉 .NET、Azure 、容器化、Azure OpenAI 與生成式AI應用解決方案，曾任微軟 TechDay、Devdays、MWC、MOPCON 等研討會講師。
共同著作：
- LangChain 奇幻旅程：OpenAI x Gemini x 多模態應用開發指南
- 極速 ChatGPT 開發者兵器指南：跨界整合 Prompt Flow、 LangChain 與 Semantic Kernel 框架
- 駕馭 ChatGPT 4: 探索 Azure OpenAI 與 Cognitive Service for Language 開發實踐 （使用 .NET 與 Node.js）
- 議程：AI Agent 初體驗
- 議程簡介： 生成式AI熱潮從文字生成發展至近期開始被討論觀注的AI Agent議題，那什麼是AI Agent，該怎麼做AI Agent，AI Agent與過去的GPTs，外掛Plugins有什麼差異，AI Agent 真的很神嗎 , 透過範例來了解AI Agent的實作過程以及解答上述疑惑
From Executor to Orchestrator: The New Developer Paradigm
Format: Technical talk with live demos, code and prompt examples
Description:
The role of the developer is fundamentally changing. We're moving from being executors who write every line of code to becoming orchestrators who conduct AI agents to build complex systems. This talk, based on my essay about transitioning from traditional coding to AI orchestration, shares practical insights from a year of experimenting with multi-agent development workflows. 🔗 Essay linked here: https://pivotech.substack.com/p/from-executor-to-orchestrator-my
Through real code examples and live demonstrations, I'll walk through my evolution from using ChatGPT for learning CS50 concepts to orchestrating Claude, Gemini CLI, and NotebookLM to build complete products. You'll discover the three distinct schools of AI development I've identified through hands-on experimentation: the One-Shot method, the Incremental approach, and my hybrid Layering technique.
I'll share the workflows I use to go from customer discovery sessions to deployed applications, including the mistakes, frustrations, and breakthroughs that shaped my approach. We'll explore the "Legacy Codebase Problem" that emerges from AI-generated code, the "Hyper-specificity Paradox" of detailed prompting, and the new skill set required to become an effective AI orchestrator.
Key Takeaways:
Three proven patterns for AI-assisted development and when to use each
Practical orchestration workflows for complex projects
The emerging skillset of the developer-orchestrator
How to maintain technical depth while leveraging AI efficiency
Real-world pitfalls and how to navigate them
Target Audience: Developers looking to evolve their practice in the age of intelligent agents. Minimal level of AI development experience required e.g. prompting Claude
Nkechi AnyanwuPlatform Sponsors
Torc is a community-first platform bringing together remote-first software engineer and developer opportunities from across the globe. Join a network that’s all about connection, collaboration, and finding your next big move — together.
Join our community today!
Don't let broken lines of code, busted API calls, and crashes ruin your app. Join the 4M developers and 90K organizations who consider Sentry “not bad” when it comes to application monitoring. Use code “guild” for 3 free months of the team plan.
https://sentry.io
Get in touch!
hi@guild.host