Databases in the Age of Vibe Coding: The Minimum Knowledge You Need to Know When Building Services with AI

🚀 In an era when AI generates SQL,
you need to understand databases to evaluate the results.

AI can help you build screens and features quickly. However, if the database’s table structure and relationships are incorrect, JOIN results can be inflated, queries can become slow, and only some of multiple operations may be applied.

The problem is not that there are no tools to write SQL for you. It is that you lack the criteria to decide what data to store under which rules, how to connect it, and what to use to verify the results.

In this course, you will learn by directly executing everything from the basics of databases—table structures—to modeling, SQL fundamentals, indexes, and transactions using MySQL and DBeaver.

Understand tables → Design relationships → Validate SQL → Check performance → Ensure data reliability

The Moment an AI-Built Service Starts to Falter Because of Its Data

Even features that worked well on the screen reveal unexpected problems as real data accumulates.

• After a JOIN, the number of rows increases, inflating sales figures and counts.

• Without required values and foreign key rules, invalid data is stored.

• As the data grows, queries that used to work fine suddenly become slow.

• The order was created, but the inventory deduction failed, causing the data to become inconsistent.

Problems like these can only be solved by first understanding table structure and relationships, performance, and units of work, rather than focusing on a single line of syntax.

Rather than memorizing syntax, we build and verify it ourselves.

Learn every topic through the flow of why it is needed → when to use it → how to structure it → how to verify the results.

• Run them directly using MySQL and DBeaver.

• We use sample shopping mall data to examine the structure and results.

• AI’s answers are also verified against the execution results and data structure.

Related skills: SQL, ERD, database, data-modelling, MySQL, dbeaver, artificial intelligence (AI)

Execute SQL directly with MySQL and dbeaver, design database structures using ERD and data-modelling, and verify the results generated by artificial intelligence (AI).

You will be trained not to stop at typing along, but to explain why these results occurred.

Recommended for people like these

This course is for people who, rather than simply knowing a lot of code, want to build services with AI or work with data while being able to independently assess the structure and results.

After completing the course, you will be able to make these judgments.

• You can read tables, columns, data types, PKs, and FKs and implement them directly in DDL.

• You can identify parent–child relationships and 1:1, 1:N, and N:M relationships in business requirements and represent them in an ERD.

• You can write core SQL such as SELECT, WHERE, GROUP BY, and JOIN, and verify the results.

• You can identify JOIN row multiplication, NULL handling issues, and incorrect aggregation levels.

• You can identify index candidates and use EXPLAIN to verify whether they are actually being used.

• You can group operations that must succeed together into a transaction and explain the flow of COMMIT and ROLLBACK.

From Fundamentals to Validation, Connected in Four Steps

We do not memorize disconnected concepts. We learn them as one continuous flow: table structure → relationships and SQL → performance and reliability → a learning method for expanding on your own.

The person who created this course

Hello. I'm developer Tani.

I have been developing web and mobile services for about 17 years and have worked on data quality verification across various projects. Currently, I serve as the CEO of Development PT, creating AI-powered services and automation tools, and share my experience with development and AI applications on the Tech Tani YouTube channel.

The faster AI writes code, the more people need the ability to define what to build and judge whether the results are correct. Rather than listing difficult terminology, I’ll demonstrate through hands-on practice why problems arise in real-world data and the order in which I check them.

Key Experience

• Current) CEO of Development PT

• Approximately 17 years of experience developing web and mobile services

• Conducted a data quality validation project

• AI Automation Tools and AI-Based Service Development

• Operating the YouTube channel TechTani, where development and AI application techniques are shared

Please check before enrolling

No prior experience with databases, SQL, or coding is required. We’ll guide you step by step, from installing MySQL to understanding table structures and core SQL.

However, this is not a course where you simply watch the videos. You will also practice by running the provided SQL yourself, checking the results, and investigating the cause when they differ from what you expected.