[NarP Series] MVC Framework in My Hands [NarP 1]

"Hello. I am Park Mae-il, an Inflearn knowledge sharer."

We are holding a live bootcamp related to Spring AI.

Quickly build your Spring AI skills and credentials, and stay ahead of AI trends.

If you would like to experience this and work on related projects, please refer to the webpage and

please consider participating.

https://itscoding.kr/

Hello. I'm instructor Park Mae-il.^^
📢 Announcement for the opening of Spring AI x Kakao PlayMCP practical course.

The only domestic practical guide to Kakao PlayMCP for Spring AI developers has begun.

✅ Perfect for those who:

• Those who want to develop AI agents with Spring Boot knowledge

• Those curious about MCP (Model Context Protocol), the latest AI standard

• People who want to register their service on Kakao PlayMCP

🛠 What will we build?

• AI counseling service 'Jamsi' based on Psalms and Proverbs

• Server with real-time data integration using @McpTool

• External deployment using ngrok and Kakao platform registration

Try developing MCP and registering on Kakao PlayMCP too!!
There's also a Kakao PlayMCP contest ongoing.
Last lecture link of the year (30% discount): https://inf.run/ELmY4
"Wishing you a year full of good things in 2026."

Title: 🤖 Still reviewing & grading assignments manually? I leave it to Spring AI! (🎁Year-end half price)

Hello developers! Aren't you tired of repetitive code reviews and assignment grading?

So I've prepared this for you! An automated system where you push code to GitHub (PR) → AI analyzes it → grades and provides feedback - I've launched (2025-12-24) the [Spring AI in Action] Build Your Own 24/7 Code Reviewer & Auto-Grading Agent course that builds this from scratch.

✅Here's what you'll build!

• Webhook: My server detects GitHub events in real-time

• Spring AI: Give AI a "strict senior developer" persona

• Async Workflow: Review and grading simultaneously! (parallel processing optimization)

• Vaadin: Even a pretty dashboard for checking scores (no frontend knowledge needed)

🎄Year-End Gift: 50% Off!🎁 Enroll now and own it for life at half price.
Grow into a 'backend developer who can handle AI' next year!

👉Check out the course:https://inf.run/q8ofE
👉Implementation video demo: https://youtu.be/E9b24Y3GNDg

🎬 [Scenario] 24-Hour Coding Classroom with AI Teaching Assistant

1. 📢 Assignment Posting (Professor)

The professor writes skeleton code for a Java assignment (Calculator.java) that students need to complete and uploads it to the GitHub repository (main branch).

"Alright, this week's assignment is to complete a calculator that finds the sum of two numbers. Variable names must be clear, and there should be no unnecessary code to get a perfect score!"

2. 👨‍💻 Working on the Assignment (Student)

The student brings the professor's repository to their own space (Sync Fork), creates a new branch (homework-1), and solves the problem.

"Hmm, a + bI just need to return that, right? All done! Time to submit it to the professor for review." The student creates a Pull Request (PR) to submit the assignment.

3. 🤖 AI Agent Activation (System)

The moment the student clicks the "Create PR" button, the dormant Spring Boot server detects GitHub's signal (Webhook) and wakes up.

• Step 1 (Analysis): The server extracts only the code changes (Diff) made by the student and passes them to the AI agent.

• Step 2 (Grading):"Hmm, the functionality is correct, but the temp variable is unnecessary. The score is 90 points!" The AI grades rigorously according to its pre-trained persona.

• Step 3 (Save): The grading result (90 points) and feedback content are securely saved in the database (DB).

• Step 4 (Feedback): At the same time, the AI leaves a comment on the student's PR. "The functionality is perfect! However, unnecessary variable declarations can waste memory."

4. 📊 View Results (Student)

The student receives a notification in just 5 seconds after submitting the PR.

"The grading is already done?"

The student accesses a dedicated dashboard (web page) and enters their GitHub ID. The screen displays the score (90 points) of the assignment they just submitted and the AI's feedback, neatly organized in tables and badges.

Hello. I'm instructor Park Mae-il.
[Season 2] Spring AI in Action: Multi AI Agent System Development course has been opened.
This is a course for Spring backend developers to develop AI Agent systems using Spring AI.
In this course, I've added order functionality, RAG, and Slack MCP integration features to [Season 1], and proceeded with development by applying the
AI Router Pattern as shown below.

I used MariaDB Vector DB to leverage the RAG recommendation feature and applied the Slack MCP Server for real-time notifications. Since various system connections are crucial for the service to operate, I hope you'll take this opportunity to create diverse Multi AI Agent services with Spring AI.
I hope you'll join us in efforts to expand Spring AI and build a foundation comparable to the Python ecosystem.

Thank you.

Course Link (30% discount link)
https://inf.run/mZhWH

Hello, I'm instructor Park Mae-il.

Spring AI in Action: Developing a Premium Reservation AI Agent Please note that the frontend implementation section is provided as additional videos in the latter part of the course.😊

Hello. This is instructor Park Maeil.
The following course has newly opened.
It's currently 30% off, so I hope those who are interested will apply and find it helpful.

[Course Launch Notification] Spring AI in Practice: Premium Reservation AI Agent Development
'Autonomous Action' Premium Reservation Agent Backend Development using Spring AI + JPA + MySQL
Beyond Chatbots to Agents: The Essentials of Tool Calling and Prompt Engineering

"ChatGPT is just the beginning! Want to transform into a real AI developer?"

💡 Course Features

• Practical AI Agent Development Using Spring AI

• Building a Robust Backend System Using JPA and MySQL

• Implementing actual business logic such as reservations, cancellations, and inquiries

• Conversation Context Memory and Prompt Engineering Know-how Transfer

This is recommended for these people!

• Those who want to integrate AI technology into backend services

• Those who want to gain practical, project-focused experience

• Those who want to master the core features of Spring AI

👉 Apply now and leap forward as a next-generation AI developer!
https://inf.run/nvaLX

This is Inflearn instructor Park Mae-il.
Me too! The lecture on how to do artificial intelligence with Spring has opened.

1. We would like to inform you that additional content has been added to the lecture.
13_Speech-based image generation with Web Speech and OpenAI (added)
Objective: Convert real-time live speech from a user using the Web Speech API and OpenAI to text, and learn to generate images via LLM.

2. The lecture material PDF file content has been added, so you can download it again.

hello everyone

This is Inflearn knowledge sharer Park Mae-il.

[Notice of opening of new lecture]

Me too! The lecture on how to do artificial intelligence with Spring has opened.

Lecture time: 14 hours and 30 minutes

Number of lectures: 64

Lecture PDF materials: Approximately 180 pages

[Course Introduction]

This course provides a practical guide to building various AI solutions using Spring Boot and OpenAI. You will develop real-world applications such as document similarity search, recommendation systems, and speech-to-text conversion without having to learn additional programming languages or AI fundamentals. Dive into the world of AI applications with Spring, focusing on solving real-world problems and creating practical solutions!

[Full Table of Contents]

01_Preparing for the practical training and issuing the OpenAI Key

Objective: Learn how to obtain an OpenAI API key and prepare to test the API in a hands-on environment.

02_Spring AI Basics and Environment Settings

Objective: Understand the concepts and structure of Spring AI, set up a development environment, and lay the foundation for Spring AI applications.

03_Chatting with OpenAI using Spring AI

Objective: Implement the ability to chat with OpenAI's GPT model using Spring AI's ChatClient.

04_Creating an image using DALL-E 3

Objective: Learn how to generate images from input text using OpenAI's DALL·E model.

05_Image analysis and math problem solving

Goal: Implement AI functions that process visual data through image analysis and solve mathematical problems based on the analysis results.

06_My own recipe made with AI

Goal: Implement AI that generates personalized recipes based on user input, leveraging OpenAI's text processing capabilities.

07_Converting voice to text (STT)

Goal: Implement a function to convert speech data to text using the OpenAI API and STT function.

08_Voice service (TTS) created with OpenAI

Goal: Build a service that outputs text data as speech using OpenAI's Text-to-Speech (TTS) function.

09_User-friendly search service (GPT+SQL)

Goal: Build a user-friendly search service that combines GPT and SQL to express database queries and search results in natural language.

10_RAG-based PDF document similarity search

Objective: Apply the Retrieval-Augmented Generation (RAG) technique to retrieve meaningful information from the database and generate reliable responses.

11_Movie recommendation system based on plot similarity

Goal: Implement a system that embeds movie plot data and recommends movies that match users' preferences through vector similarity search.

12_RAG-based hotel AI chatbot service

Goal: Implement a chatbot that uses the GPT model to understand users' questions and provide relevant information in real time through streaming.

[View lecture]

https://inf.run/S7gwA

thank you