吴恩达 Agentic AI 第一讲Welcome!
By kouzi-bolt
Summary
## Key takeaways - **Coined 'Agentic AI' Term**: When I coined the term agentic to describe what I saw as an important and rapidly growing trend in how people were building on-based applications, what I did not realize was that a bunch of marketers would get hold of this term and use it as a sticker and put this on almost everything in sight. [00:01], [00:23] - **Hype Skyrockets, Apps Grow Rapidly**: Ignoring the hype, the number of truly valuable and useful applications built using agentic AI has also grown very rapidly, even if not quite as rapidly as the hype. [00:24], [00:48] - **Agentic Apps: Support to Diagnosis**: Today, agentic workflows are being used to build applications like customer support agents, or to do deep research to help write deeply insightful research reports, or to process tricky legal documents, or to look at patient input and suggest possible medical diagnoses. [00:48], [01:28] - **Impossible Without Agentic Workflows**: On many of my teams, a lot of the projects we built just would be impossible without agentic workflows. [01:05], [01:28] - **Key Skill: Evals and Error Analysis**: It turns out that one of the biggest differences I've seen between people that really know how to build agentic workflows compared to people that are less effective at it is the ability to drive a disciplined development process, specifically one focused on evals and error analysis. [01:28], [01:51]
Topics Covered
- Hype Masks Real Agentic Growth
- Agentic Powers Impossible Apps
- Master Evals to Build Agents
Full Transcript
Welcome to this course on Agentic AI. When I coined the term agentic to describe what I saw as an important and rapidly growing trend in how people were building on-based applications, what I did not realize was that a bunch of marketers would get hold of this term and use it as a sticker and put this on almost everything in sight. And that has caused hype on Agentic AI to skyrocket.
The good news, though, is that Ignoring the hype, the number of truly valuable and useful applications built using agentic AI has also grown very rapidly, even if not quite as rapidly as the hype. And in this course, what I'd like to do is show you best practices for building agentic AI applications and just open up a lot of new opportunities to you in terms of what you can now build. Today, agentic
workflows are being used to build applications like customer support agents, or to do deep research to help write deeply insightful research reports, or to process tricky legal documents, or to look at patient input and render or to suggest possible medical diagnoses. On many of my teams, A lot of the projects we built just would
diagnoses. On many of my teams, A lot of the projects we built just would be impossible without agentic workflows. And so knowing how to build applications with them is one of the most important and valuable skills in AI today. It turns out that one of the biggest differences I've seen between people that really know how to build agentic workflows compared to people that are less effective at it is the ability to
drive a disciplined development process, specifically one focused on evals and error analysis. And
in this course, I'll tell you what that means and show you what allows you to be really good at building these agentic workflows. Being able to do this is one of the most important skills in AI today and will open up a lot more opportunities, be it job opportunities or opportunities to just build amazing software yourself.
With that, let's go on to the next video to dive more into what are agentic workflows.
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