Developing LLM Applications Using RAG (feat. LangChain)

I'm excited to share some great news with all of you who have been learning and growing together through my AI agent development course. My first book, which compiles the in-depth content and practical essentials that couldn't be fully covered in the lectures, has finally been published. This book focuses on addressing the most frequently asked questions from the classroom and solving real-world challenges.

As I've always emphasized in my lectures, the key to agent services is not simply 'implementing' features, but 'proving' their performance.

During the writing process, as I experienced rapid technological changes such as EXAONE 3.0 being updated to 3.5 and changes in the Ollama support environment, I became convinced once again. What matters is not 'trends' but 'fundamentals'. That's why the final chapter of this book focuses intensively on the [Evaluation] part, which I consider most important.

For those who want to manage agent performance with objective metrics rather than subjective feelings, this book will serve as an excellent guide.

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🎓 'Next Step' Preview for Course Students

The book solidly covers the theoretical foundation and core principles of evaluation. However, you may be curious about how to automate and operationalize this in practice. To address this, we are separately preparing a course that includes the following advanced content.

• Establishing evaluation policies using LangSmith

• Writing and optimizing Evaluators in production environments and their practical applications

• Sustainable LLM Application Improvement Process

After building a solid theoretical foundation through the book, I recommend experiencing 'the completion of evaluation' through the hands-on lectures that follow.

Now available for pre-order at the bookstores below.

• [Kyobo Book Centre]: https://product.kyobobook.co.kr/detail/S000218961185

• [Aladin]: https://www.aladin.co.kr/shop/wproduct.aspx?ItemId=383332045

• [Yes24]: https://www.yes24.com/product/goods/172726927

Hello, I'm Kang Byeong-jin.

Hello, I recently had a great opportunity to participate in And Studio's 'Ace Report' to share my career story.

I'm facing a new beginning, but rather than this video covering the know-how of transitioning to big tech companies, it has become a space where I calmly share the thoughts I've pondered and experienced while approaching work over the years.

Looking back, I think my career has been closer to failure than success. There were experiences of starting and closing businesses that aren't recorded on LinkedIn, and moments of rejection that far outnumbered acceptances. However, I believe I am who I am today because of the learning and lessons I gained through that process.

While the title 'Work Expert' is a bit embarrassing, I hope my story of constantly challenging myself and learning from those experiences can reach and help those who have similar concerns.

Thank you for taking the time to watch, and it would be a great help if you could share your thoughts about the video.

https://youtu.be/UR9PL1Jz-qs?si=nYUszHC3GrU21K-Q

Thank you to all the students taking this course, and if you encounter any parts where the explanation is insufficient, parts that are difficult to understand, or difficulties you face when applying this to your actual work, please post them as questions and I will respond as quickly as possible.

Thank you

Best regards, Kang Byeongjin

Hello, I'm Kang Byeong-jin.
First, I sincerely thank all the students who have taken my courses and always send good feedback and encouragement.
Thanks to all of you, I have been able to consistently continue my lectures and AI-related activities. 🙏

Tomorrow, Wednesday, August 13, 2025 at 9 PM, I will be appearing on TeddyNote Live
to discuss the topic "When and How Should Companies Utilize AI?"

In this live session

• Real-world AI/LLM practical application cases based on actual experience

• Considerations and Tips When Introducing AI to Work

• Real-time Q&A to resolve your questions

and more will be shared honestly.

📅Broadcast Schedule: Wednesday, August 13, 2025, 9 PM
📍How to Participate: TeddyNote YouTube Channel Live: https://www.youtube.com/live/tqOkjsVzoSo

I'm very excited to be able to communicate in real-time with those I've only met through lectures until now.
I hope this will be a time to share your questions, concerns, and ideas together.

We ask for your interest and participation,
and we'll see you in the live session!

— Best regards, Kang Byeongjin

Are you thinking about developing/operating an LLM service? Our company is planning to hold a meetup to share LlamaIndex and LLM development/operation know-how, so we are providing you with the relevant information~

The 2nd GenAI Connect Day, an LLM Workshop for developers who operate or plan to start an LLM service, will be held on September 26th at GS Tower. This event is hosted by GS Group’s Open Innovation Community 52g in collaboration with LlamaIndex and Pie&AI from DeepLearning.AI. LlamaIndex’s AI Engineer Pierre-Loic Doulcet will present on-site, and Liner’s Hoon Heo and AutoRAG researcher Jeffrey Kim will share their know-how and insights related to LLM service development. We hope you will gain a lot of insights from AI engineers in various fields and have networking opportunities at the after-beer party!

[Guide] GenAI Connect Day #2: LlamaIndex x 52g

📅 Date: 6:30 PM, Thursday, September 26, 2024

🏢 Location: Keeeet Open Hall, 25th floor, GS Tower

👍 Target: Developers who are developing services using LLM

🚨 Application Period: 2024. 9. 9 (Mon) ~ 2024. 9. 24 (Tue)

✅ Speaker introduction and application link: https://bit.ly/52g-genai-2

🚀 Inquiry: GS Corp. Manager Byungjin Kang ( jason.kang@gs.co.kr )

Although it is not officially(?) announced, we are planning to prepare various products for developers, so please show a lot of interest!

Hello, this is Kang Byeong-jin.

It hasn't been long since I launched the course, but I'm seeing a lot more people taking the course and asking questions than I expected.
One of the most common questions we got was OpenAI API quota를 어떻게 늘리느냐 .

So I did some additional filming on how to increase your OpenAI API quota, but then I realized you've already paid for the course.
We realized that you might not want to pay for the OpenAI API, so we added a way to use the Upstage API, which gives you $30 in credit when you sign up.

Those who have taken the course already know that UpstageEmbedding is much more performant than OpenAIEmbedding for embedding, so I think you may get better results by taking the course.

I would like to express my gratitude to those who actively asked questions for their good feedback. If there is anything you do not understand or find difficult while taking the class, please ask questions! I will try to answer as quickly as possible.

thank you
Kang Byung-jin's dream

Hello, this is Kang Byeong-jin.

We have recently released a course on constructing RAG using the popular Large Language Model (LLM).

This is my main job at my company these days, and I've been struggling with this since last year... I prepared this lecture in the hopes that others will have a little less trouble.

The lecture utilizes the OpenAI API, and since it utilizes LangChain, you can easily follow along by using packages that utilize LangChain, such as Claude, Cohere, Upstage, etc. If you look at the lecture content, you can use ChatAnthropic , ChatCohere , ChatUpstage , etc. for the parts corresponding to llm in LCEL, and if you want to utilize Llama3 by utilizing Ollama , you can use ChatOllama .

If you need a lecture using Ollama or want to know more about LLM, please leave a review or question about the lecture or send me an email to jasonkang14@gmail.com . It will be helpful for me to prepare the next lecture!