RAG for an LLM Service by a Silicon Valley AI Developer

You know about AI agent frameworks, but understanding how they work and applying them in practice can be difficult, right? Drawing on firsthand experience from Silicon Valley, we’ll guide you from the core principles to practical applications.

This is a Redis course created with a current Kakao interviewer. It covers everything from data structure practice (String to Sorted Set) to Sentinel and Cluster configurations, helping you build design rationales that work in both interviews and real-world practice.

It was created to solve the "overwhelming problem of not knowing where or how to start with Kubernetes." Based on hands-on experience operating financial infrastructure, it is designed to help you understand the actual build and operation flow rather than just simple theory. Through a learning process that covers the relationship with Docker, YAML, Pods, Deployments, and Services, learners will master Kubernetes not just as a "concept," but as a "usable skill."

This course goes beyond simple CRUD-level database usage to help you acquire PostgreSQL skills necessary for the AI era from a practical perspective. Based on AI development experience in Silicon Valley, you will learn step-by-step how to design and utilize JSON, indexes, transactions, and even pgvector in real-world services, while mastering methods to solve complex data structures and performance issues.

This course goes beyond simply teaching you how to use Docker as a tool; it approaches the subject from the perspective of solving the real-world dilemmas and problems encountered in professional practice. From unpredictable errors caused by differences between development and production environments, to configuration mistakes stemming from vague concepts of images and containers, and even the anxiety of "how much do I need to know to survive in the field"—this course explains it all based on firsthand experience operating financial infrastructure. Rather than just listing commands, it focuses on real-world cases: why certain structures are necessary, how to design images for easy maintenance, and how to handle containers for stable service operation. In particular, by prioritizing hands-on practice over theory, the course is designed to elevate students from simply "knowing how to use" Docker to "understanding it from an operational perspective" through visual comprehension and direct experience. This course provides practical standards and direction for those new to Docker, those who have used it but lack a clear conceptual grasp, and developers looking to take their infrastructure intuition to the next level.

Build a scalable real-time event streaming order processing system using Spring Boot 3.x + Kotlin, establishing a Kafka cluster, and leveraging PostgreSQL CDC, Debezium Connect, and Apache Avro schemas.

Kotlin mastery via virtual payment server course.

This course covers RPC communication techniques to maximize performance in large-scale MSA (Microservice Architecture) environments. Beyond simple gRPC practice, you will learn how to implement stable and efficient inter-service communication in real-world production environments where hundreds of microservices operate simultaneously. Based on Golang, the curriculum focuses on practical applications, including writing Protocol Buffers (proto) syntax, automated code generation and service implementation, the structure of gRPC and its advantages over traditional RPC, and performance optimization strategies. Designed to be easily understood even by non-majors or entry-level server developers, the course explains everything from the basic concepts of RPC to the internal workings of gRPC step-by-step, helping you build practical skills that can be applied immediately to real services.

Systematically learn the distributed NoSQL database Cassandra, from basic concepts to practical application. Develop high-volume data processing capabilities through practice-oriented theory and hands-on exercises, including data modeling, query optimization, and cluster configuration. Even without prior database experience, you can grow into a Cassandra expert based on the know-how of a current Silicon Valley developer.

When you find yourself constantly updating Swagger documentation, aligning API specs, and repeatedly communicating with the frontend, you start to wonder, "Why am I doing the same thing twice?" I also felt similar frustrations in my professional experience, which led me to use GraphQL extensively and develop an interest in data-centric design. This course goes beyond simple GraphQL syntax; it explores the real-world problems it was created to solve, along with practical considerations like Resolver structures, the N+1 problem, and Federation. I've structured this course to help you naturally learn how to reduce communication costs between developers and design more flexible API structures.

The biggest challenges in operating batch systems that process millions of records are performance degradation and the difficulty of recovery in the event of a failure. These issues cannot be solved with simple loops or poor design. Based on my experience of reliably processing large-scale data in real-world service environments, this course covers the structure and operating principles of Spring Batch and provides design methods to achieve both performance and stability. Moving beyond simple functional descriptions, this course will help you develop fundamental data processing problem-solving skills through batch architectures that can be applied immediately in practice.

This course is for developers who want to find fundamental solutions in environments where response times slow down as traffic increases, thread pools are quickly exhausted, and bottlenecks worsen with more external API calls. It helps you look at problems from the perspective of changing the architecture itself, rather than simply scaling out servers. Through this course, you will first understand the limitations of the traditional Spring MVC "Thread per Request" model. You will examine at the code level why throughput doesn't increase even when CPU resources are available, and exactly how blocking I/O occupies system resources. Next, you will learn the concepts and standard specifications of Reactive Streams and master how to handle data streams using Reactor's Mono and Flux. Beyond simple usage, you will learn through hands-on practice how data flows start, how they are consumed, and how throughput is controlled. In particular, you will directly implement design patterns that prevent OOM (Out of Memory) or overloads using Back Pressure. Additionally, you will understand the event loop-based processing structure of Spring WebFlux and conduct comparative exercises on how Non-Blocking I/O operates during actual request processing. By placing MVC and WebFlux side-by-side to verify their structural differences, you will also establish criteria for when to choose Reactive. This goes beyond simply "learning asynchrony." You will learn how to handle more requests with fewer threads, how to maintain a stable flow in environments with high external API dependencies, and develop the design intuition to secure throughput in high-concurrency environments.

This course focuses on solving the problem of getting stuck in interviews and practical work due to a lack of understanding of why certain structures and configurations are necessary, rather than just teaching how to configure NGINX. Based on experience evaluating numerous candidates as an interviewer for companies like Naver, Kakao, and Toss, I explain how to describe and utilize NGINX from the perspectives of performance, scalability, and operations through hands-on practice. The core of this course is to help you develop a mindset capable of tracing traffic flow and troubleshooting problems, rather than just memorizing configuration values.

This course was created to solve a common problem many people face while preparing for developer jobs: "I studied CS and data structures, but I get tongue-tied during interviews." While conducting actual interviews at companies like Naver, Kakao, and Toss, I noticed that most candidates have memorized concepts but cannot explain why those concepts are necessary or how they are applied in real-world situations. Rather than simple rote memorization, this course teaches you how to understand the interviewer's intent and provide more persuasive answers to the same questions. Whether it's the OSI 7 layers, data structures, or coding tests, we focus on why you need to know them, when they are used, and how to speak about them to receive a positive evaluation in an interview. This course is for those who want to become developers who can explain what they understand in their own words, rather than just giving the same answers as everyone else.

Most developers are still stuck on Batch and CronJobs when it comes to data processing. However, in real-world production environments, data is generated continuously, and failing to process that flow immediately leads to latency, bottlenecks, and consistency issues. Having personally dealt with real-time recommendations, state synchronization, and event delay problems in high-traffic environments, I’ve often asked myself, "Is batch processing really the right approach for this?" This course begins with that very question. It explores how to use Apache Flink to perform computations the moment data flows, manage state securely, and produce accurate results based on Event Time—all from a practical perspective. Beyond simple theoretical explanations, you will experience how real-time stream processing systems are designed and operated through actual source code and architectures. For those who found real-time processing vague or were curious about the world beyond messaging, this course will provide a clear sense of direction.

At some point in backend development, you start to have these concerns. It's that moment when services expand and traffic increases, and you begin to feel the limitations of simple REST communication and CRUD structures. I experienced these same issues in the field and went through much trial and error balancing performance and structural complexity. The solution I chose during that process was NATS. Its simple configuration based on a single binary, ultra-low latency performance in microseconds, and the fact that it provides essential features—from Pub/Sub to Queue Groups and JetStream—without being overkill made it a very practical choice for real-world service environments. This course is not just a list of NATS features. Based on the problems I faced in practice, I explain through code and workflows why I chose NATS in certain situations and how I designed the architecture. This course is designed to help everyone—from those new to messaging systems to backend developers preparing for employment and senior developers considering better architectures—understand distributed systems and grow to the next level.

This course breaks down microservice architecture and distributed environments not as a mere list of technologies, but through the "design perspective" required in actual practice and interviews. Starting from the differences between Monolithic and MSA, it covers gradual migration strategies, Modular Monoliths, Clean Architecture, and Hexagonal Architecture step-by-step, clearly explaining why each choice is necessary and the resulting trade-offs. Furthermore, through hands-on practice, you can directly verify the intent of the structures and learn about core issues inevitably encountered in distributed environments—such as data consistency, transactions, inter-service communication, and fault tolerance—through realistic scenarios. Based on the actual questions and perspectives of a Kakao interviewer, this course aims to go beyond simple knowledge acquisition and elevate your very way of thinking about distributed systems to the next level.

This course provides a step-by-step learning path, ranging from the fundamental usage of MySQL to advanced techniques required in real-world production environments. It covers a wide range of topics, including data modeling techniques based on various case studies and practical data, evaluating the effectiveness of Foreign Key designs, analyzing Google Calendar schema DDL, and modern DDL design principles. Through this course, you will gain an in-depth understanding of how to utilize MySQL as a core system component rather than just a simple database.

Learn the SAGA transaction management technique for maintaining data consistency in distributed environments through a hands-on approach. You will configure three microservices using Spring Boot and Docker, and implement both Orchestration and Choreography patterns using Kafka and MySQL. Through this course, you will master core concepts applicable to real-world scenarios, including the operational principles of distributed transactions, designing compensating transactions, and handling fault recovery.

Learn the process of building essential Observability in a Microservices Architecture (MSA) environment, from the basics to practical application. You will master standardized data collection using OpenTelemetry, trace storage and search via Grafana Tempo, and visualization using TraceQL through step-by-step hands-on exercises. You will learn how to track service flows, identify bottlenecks, and analyze the root causes of failures through distributed tracing.

This course is part of the 'Wrtn AI Literacy Voucher Program', a collaboration between Inflearn and Wrtn, and is available completely free for seniors (60+) who are vulnerable to AI adoption. *Priority for people with disabilities Are you curious about AI but unsure how to get started? This course is an introductory program designed to help seniors start learning AI comfortably and enjoyably. Join instructor Choi Jin-young to create text, images, and even videos using AI tools like Wrtn!

Understand Transformer-based LLM architectures and GPU utilization strategies, and gain hands-on experience with the actual serving process using vLLM. This course covers the entire practical workflow, from building AI system pipelines to monitoring and multi-GPU utilization, and is designed for intuitive understanding through diagrams and practice without complex formulas.

Acquiring probability theory is essential in the study of AI and machine learning. I recommend this to those who wish to study probability theory in more depth.

Core Principles of n8n Automation and Workflow Design Basics for Non-Majors 5-Step Automation Built with n8n: API Connection Practice from Topic Input to Video Completion How to Automatically Create Videos in n8n Using AI APIs (ChatGPT, ElevenLabs, Creatomate)

Turn your dormant "notebook" into an "AI Workspace" that works on its own! Connect Notion DB with agents to complete a system where repetitive tasks run themselves.

How does the architecture change when an LLM is integrated into an existing backend? This is an introductory system design course that goes beyond simple LLM API calls to help you understand core AI service components such as Model Routers, LLM Gateways, and Vector DBs, and step-by-step design an operational AI service architecture including RAG and AI Agents. It is designed to help those who want to create their own LLM-based AI services quickly master the design workflow.

Put an end to daunting data analysis with ‘Exploratory Visualization’! Drastically increase the speed of practical analysis without difficult coding.

This is an 18-lesson course across 5 modules designed to transform Generative AI LLM agents—which often drain money through API costs—into a profitable structure by controlling expenses with model routing, cascading, caching, and loop guardrails. You will personally build everything from analyzing real-world cases of "cost bombs" to profit-and-loss simulations and architecture design projects. We recommend this course to AI developers and makers burdened by API costs, as well as those planning or operating agent-based services.

Stop paying for student record design. I will reveal all the consulting secrets used directly by an admissions consultant with 30 years of experience.

This is a recording of a meetup with CEO Yongho Ha, who has been at the center of the AI evolution—from starting as a first-generation data scientist to achieving two machine learning startup exits and serving on the National AI Strategy Committee. Have you ever felt that the more you use AI, the more unclear your own expertise becomes? We’ve all been there. This anxiety stems from "Workslop" and the technical, cognitive, and intentional debt that accumulates without us even realizing it. This meetup begins by diagnosing the true nature of this anxiety and moves on to practical discussions for working with stability—covering everything from verification skills and structural design to learning methods for building your own criteria for judgment.

There may be people who have never taken my lecture, but no one has taken it only once. After teaching in person for so long, I have finally had the opportunity to create this online course. Since the commercialization of AI, I have produced and researched countless pieces of AI content. Based on that knowledge and experience, I have built a logical philosophy of my own and organized it into concepts that are easy for anyone to understand. For those who have been generating AI images without considering the underlying concepts, I will instill a proper foundation in you. Once you take this course, you will be able to create any AI image in the future. Have you never created an AI image before? That’s perfectly fine. You don't need any prior experience in AI image generation. By simply learning and practicing through this lecture, you can become an expert in AI content creation.

Developing AI Applications with Spring Boot and Spring AI: Mastering OpenAI for Real-World Solutions

Learn how to easily integrate the ChatGPT API using Spring AI and develop an AI server through prompt engineering!!

In an era where AI writes code for you, will you remain a 'Coder' or leap forward to become an 'Architect'? This course is designed for junior developers who can handle basic implementation but feel stuck about the next steps or are anxious about falling into the trap of 'fake experience'. We aim to go beyond simply learning clean architecture theory and turn Robert C. Martin's (Uncle Bob) high-level design principles into weapons for the AI era.

This is a course to learn large-scale traffic processing and real-time streaming through practical projects by integrating RabbitMQ, Kafka, and Redis with Python Flask.

Regardless of the field! This is a lecture that covers the core fundamentals that developers must know in practice in an easy + code-oriented way. I highly recommend this lecture to all junior developers and job seekers who want to grow.

The shipbuilding and maritime industry is a representative field of traditional heavy industry, but it is securing new competitiveness through the combination of digital transformation and artificial intelligence (AI) technology. This course is structured around specific application cases actually used in the field, such as AI-based shipyard production management, ship design automation, maritime logistics optimization, and predictive maintenance system construction. With a field-centered approach, you can understand not just simple theory but **'how AI actually works in shipyards'**. Additionally, it covers data infrastructure construction, model training, and constraints specific to the marine environment that must be considered during the AI technology implementation phase.

This course is a practical program where you will master Kotlin-based AI agent development by building your own coding agents. Using Koog, an AI framework built with Kotlin, you will learn step-by-step how to implement coding agents similar to Claude Code, Cursor, and Junie. Koog is more than just a simple server-side framework; it integrates seamlessly with Spring and offers the scalability to connect with various environments—including Android, iOS, Desktop, and Web—through Kotlin Multiplatform (KMP). By building intelligent agents that can read, analyze, modify, and generate code, you will gain hands-on experience in AI agent architecture, strategy, context handling, and tool integration.

The Gemini agent that works across Google Drive! Put the finishing touches on your Google AI workflow with overwhelming productivity.

This is a practical course on 'AI-based Circuit Design/Verification Automation' as required by professionals at Samsung Electronics and SK Hynix. Master the skills for LDO IP design and verification automation based on TSMC 180nm PDK, AI-based AXI-Lite RTL implementation, and Python/TCL/Batch script regression automation.