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Podcast
4 episodes
2025-09-22
AI Agent - From Code to Insight: A Practical Look at Building GPT Agent-like
留言告訴我你對這一集的想法： https://open.firstory.me/user/cmfhwlyqs01kb01tjglmp9uu4/comments Don't you think the whole AI Agent idea is just amazing? An AI Agent is so much more than just a chatbot window. It's like it can actually think for you, get tasks done, and then give you a neat summary of the results. We can start with the basics by building our own AI Agent, chose the GPT Agent as our reference. This simple project will help us really understand the core elements of a great AI Agent: Reasoning, Planning, and Tool Use. From there, we can look at more advanced features to make it even better, like Memory, Reflection (which is like self-correction), and Perception. It's pretty cool when you think about it—if you look closely, GPT has been an agent all along, even from the very beginning. It doesn't just answer your questions; it follows a whole process of reasoning, planning, and using tools to get you what you need. I hope this gives you a better sense of what an AI Agent is all about. Feel free to reach out anytime to chat more and keep exploring this fascinating world together!
2025-09-22
AI 代理 – AI Agent 實作探索與啟發(以類GPT Agent為例)
留言告訴我你對這一集的想法： https://open.firstory.me/user/cmfhwlyqs01kb01tjglmp9uu4/comments 你是不是也覺得 AI Agent 這個概念超酷的？一個AI Agent，不單單只是一個聊天的視窗。 他不只像是可以思考，還能幫你執行一些工作，最後給你一些彙整與結果。 從最基本的概念開始，做一個AI Agentic Application來探討實際上他實作的方法與要點。 這裡我們以GPT Agent為對象也去實作一個自己的AI Agent，從這個簡單實例當中清楚感受到AI Agent很常見的幾大要素：Reasoning (推理)、Planning (規劃)、Tool Use (工具使用)。 也延伸思考可以繼續細化這個服務的幾個面向：Memory (記憶)、Reflection (反思 / 自我修正)、Perception (感知)。 這很有趣，如果你仔細觀察，會發現我們從一開始接觸 GPT 的時候，它就已經是個 Agent 了。它不只會回答你的問題，還會根據你的需求，去執行一系列的推理、規劃和使用工具的動作。 希望這個簡單的介紹能讓你對 AI Agent 有更深的認識，歡迎隨時一起交流，繼續探索這個有趣的世界！
2025-09-13
AI Coding + Product Development: Faster, Different, Better? (with Gemini CLI)
A Introduction + Summary of my study recentlly:AI Coding + Product Development: Faster, Different, Better? (with Gemini CLI) Full article go ahead check in my nice-neil.com. thanks. - In today's fast-moving digital world, a big question is on everyone's mind: How will AI change our jobs, especially in the software industry? I've been looking into how AI coding affects product development, using Google's Gemini CLI as a test case to find some real-world answers. This isn't just about new technology. It's about how our software teams will be built from now on. In this article, I'll share what I've learned, discussing whether AI coding helps us build products faster, better, or in new ways. I'll also share over 10 real situations with AI coding. After my tests, my first conclusion is that AI coding's main value is giving us a more efficient way to generate code. It can quickly and automatically handle repetitive and time-consuming coding tasks, which lets us focus on bigger goals for the product. However, while AI is great at generating code, it has clear limits when it comes to understanding human meaning, logic, and making key decisions. This means the role of a human engineer is changing from a simple "programmer" to an "AI conductor." We still need a human-in-the-loop. For product managers, AI is a great opportunity. It can automate some tasks and help them build tools for efficiency, like drafting initial technical documents or creating team management tools. All of this gives product managers more time for market research, user interviews, and planning strategy—all of which lead to more valuable products. However, using code generated by a product manager with AI for actual production to go alive is still a long way off. It requires a lot of help from engineering knowledge to make sure it's efficient and on the right way. The arrival of AI coding points to a future where our roles will be upgraded. Product teams will need more people who are a mix of technical and creative talent, people who can use AI tools effectively. AI coding is just one part of this change. A product manager's job has many other areas that can be improved with AI tools. We're heading toward a clear future of more efficient and creative work.
2025-09-22
AI Agent - From Code to Insight: A Practical Look at Building GPT Agent-like
留言告訴我你對這一集的想法： https://open.firstory.me/user/cmfhwlyqs01kb01tjglmp9uu4/comments Don't you think the whole AI Agent idea is just amazing? An AI Agent is so much more than just a chatbot window. It's like it can actually think for you, get tasks done, and then give you a neat summary of the results. We can start with the basics by building our own AI Agent, chose the GPT Agent as our reference. This simple project will help us really understand the core elements of a great AI Agent: Reasoning, Planning, and Tool Use. From there, we can look at more advanced features to make it even better, like Memory, Reflection (which is like self-correction), and Perception. It's pretty cool when you think about it—if you look closely, GPT has been an agent all along, even from the very beginning. It doesn't just answer your questions; it follows a whole process of reasoning, planning, and using tools to get you what you need. I hope this gives you a better sense of what an AI Agent is all about. Feel free to reach out anytime to chat more and keep exploring this fascinating world together!
2025-09-22
AI 代理 – AI Agent 實作探索與啟發(以類GPT Agent為例)
留言告訴我你對這一集的想法： https://open.firstory.me/user/cmfhwlyqs01kb01tjglmp9uu4/comments 你是不是也覺得 AI Agent 這個概念超酷的？一個AI Agent，不單單只是一個聊天的視窗。 他不只像是可以思考，還能幫你執行一些工作，最後給你一些彙整與結果。 從最基本的概念開始，做一個AI Agentic Application來探討實際上他實作的方法與要點。 這裡我們以GPT Agent為對象也去實作一個自己的AI Agent，從這個簡單實例當中清楚感受到AI Agent很常見的幾大要素：Reasoning (推理)、Planning (規劃)、Tool Use (工具使用)。 也延伸思考可以繼續細化這個服務的幾個面向：Memory (記憶)、Reflection (反思 / 自我修正)、Perception (感知)。 這很有趣，如果你仔細觀察，會發現我們從一開始接觸 GPT 的時候，它就已經是個 Agent 了。它不只會回答你的問題，還會根據你的需求，去執行一系列的推理、規劃和使用工具的動作。 希望這個簡單的介紹能讓你對 AI Agent 有更深的認識，歡迎隨時一起交流，繼續探索這個有趣的世界！
2025-09-13
AI Coding + Product Development: Faster, Different, Better? (with Gemini CLI)
A Introduction + Summary of my study recentlly:AI Coding + Product Development: Faster, Different, Better? (with Gemini CLI) Full article go ahead check in my nice-neil.com. thanks. - In today's fast-moving digital world, a big question is on everyone's mind: How will AI change our jobs, especially in the software industry? I've been looking into how AI coding affects product development, using Google's Gemini CLI as a test case to find some real-world answers. This isn't just about new technology. It's about how our software teams will be built from now on. In this article, I'll share what I've learned, discussing whether AI coding helps us build products faster, better, or in new ways. I'll also share over 10 real situations with AI coding. After my tests, my first conclusion is that AI coding's main value is giving us a more efficient way to generate code. It can quickly and automatically handle repetitive and time-consuming coding tasks, which lets us focus on bigger goals for the product. However, while AI is great at generating code, it has clear limits when it comes to understanding human meaning, logic, and making key decisions. This means the role of a human engineer is changing from a simple "programmer" to an "AI conductor." We still need a human-in-the-loop. For product managers, AI is a great opportunity. It can automate some tasks and help them build tools for efficiency, like drafting initial technical documents or creating team management tools. All of this gives product managers more time for market research, user interviews, and planning strategy—all of which lead to more valuable products. However, using code generated by a product manager with AI for actual production to go alive is still a long way off. It requires a lot of help from engineering knowledge to make sure it's efficient and on the right way. The arrival of AI coding points to a future where our roles will be upgraded. Product teams will need more people who are a mix of technical and creative talent, people who can use AI tools effectively. AI coding is just one part of this change. A product manager's job has many other areas that can be improved with AI tools. We're heading toward a clear future of more efficient and creative work.