Vibe Coding FullStack with Spring Boot 4, React Using Junie

Learn the foundations of vibe coding using AI-enabled agentic coding tools, explore tools like Junee, discuss best practices, and preview JetBrains AI and Junee workflows.

Explain why AI coding tools matter for software development, boosting productivity and enabling large-scale code generation with models like GPT-4 and Junie, while emphasizing review.

Explore vibe coding, a new approach where you describe your software idea in plain language and an AI model generates and guides the code, enabling non-developers with responsible use.

Explore vibe coding tools across IDE plugins and web platforms, featuring AI-assisted code completion, file generation, and project-wide context, with Juni by JetBrains and Java Spring emphasis.

Explore vibe coding best practices by refining prompts, writing unit tests, and iterating with version control, using popular languages and rules to guide AI tools.

Introduction to Junie shows how to use the IntelliJ-integrated tool to automate coding tasks, switch between ask and code modes, and edit files in brave mode with Spring Boot.

Explore vibe coding and how JetBrains AI tools, including Junee, boost full-stack development with Spring Boot and React. Install these tools, review security considerations, and document OpenAPI endpoints with Genie.

Explore JetBrains' AI plans and credits, including free, AI Pro, and AI Ultimate, and install the JetBrains AI assistant and JetBrains Junior plugins after logging in.

Explore JetBrains AI alongside Juni, using plain-English prompts to generate tests and refactor the current class, acting as a junior coding assistant within your project.

Create a Spring Boot project in IntelliJ via Maven with Java 21, add Lombok, Spring Web, Spring MVC, Spring Data JPA, H2, Flyway, Jakarta Validation; review and set up Junie.

Create a JPA entity named Beer on a feature branch using Junie and Lombok for getters, setters, and constructors. Annotate created and updated date fields with Hibernate.

Create a spring data jpa repository for the beer entity and a data jpa test for basic crud operations using junie, with tests passing after configuring hibernate table creation.

Use Junie to generate a service layer, a Spring MVC controller, and tests for create, get by id, and list all endpoints backed by Spring Data JPA.

Learn to extend spring boot controllers with Junie by adding update and delete endpoints, implementing new service methods, and expanding test coverage with mock mvc and unit tests.

Explore JetBrains AI and enterprise security, covering SOC 2, ISO 27001, PCI DSS, HIPAA, GDPR, data privacy, opt-in usage, and on-prem LLM options with Hugging Face and major providers.

JetBrains trust center offers access to compliance reports, including Soc2 type two and GDPR, via NDA requests. It details encryption, unique account authentication, and penetration testing for auditor reviews.

Explore JetBrains AI with Jouni and learn to guide workflows for step-by-step code generation, scaffolding controllers and open API specifications, and create reusable prompt templates.

Explore ai-guided workflows with Juni, using markdown to structure requirements, refine prompts, and plan implementation, then refactor jpa entities to dtos with map-struct mappers.

Learn to add mapstruct as a maven dependency, fetch the latest release with JetBrains AI deep search, and configure the maven compiler plugin for Spring components with Lombok.

discover how Junie uses a root guidelines file to codify project standards, tailor AI-driven guidance, and generate a living guidelines.md for a Spring Boot app with mermaid diagrams and tests.

Learn how to use JetBrains Juni guidelines for a Spring Boot project, including selecting, adapting, and evolving living guideline files to shape naming conventions and code quality.

Update the beer controller to use a beer dto and a mapstruct mapper with Lombok, ignoring id, createDate, and updateDate when mapping; adapt surface layer input to dto usage.

Analyze the project requirements and convert them into a detailed implementation plan using Junie, refining prompts, requirements, and a plan file to guide improvements.

Directs uni to convert draft requirements into a detailed task list with Junie, generating tasks for mappers, service, and controller layers, and prepares tests and a pojo/dto pattern with Lombok.

Learn to use Junie to complete a task list by leveraging requirements, plan, and tests, updating tasks as they are completed, and reviewing changes like beer DTO and mapper.

Use Junie to analyze an ERD image and generate detailed Java development instructions for implementing beer order, beer order line, and a base entity in JPA with Lombok.

Learn when to use follow-up prompts versus new prompts, manage context and token usage, and refine prompts with Junie and Cuny guidelines.

Explore how to update Junie guidelines to support Spring Boot flyway migrations, including the default migration directory, version naming conventions, and the importance of immutable migration files and checksums.

Document your api with redoc by generating interactive openapi-based documentation; learn to lint, serve locally, and build a developer portal with code samples and interactive tryouts.

Add an OpenAPI specification to your project by importing a starter, installing npm packages, and organizing APIs with file-referenced components for modular, bundle-ready documentation.

Configure Junee to work with the OpenAPI specification and update guidelines. Inspect the OpenAPI YAML, align file references, naming conventions, and test with npm test.

Learn to automate OpenAPI documentation for a beer API by embedding DTO comments with Junie to update the spec, including beer style, 13-digit UPC, and read-only fields.

Clean up the OpenAPI specification by removing unused paths, webhooks, and references, refactor to the four paths and ensure the YAML and tests remain valid with Junie.

Add a new customer entity to a Spring project, including name, email, phone, and address fields, a one-to-many relation to beer orders, CRUD REST controller, migration, and API docs.

Perform a sprint retrospective on adding a customer entity. Identify what went well and what didn't, and propose guideline updates for h2, super builder, and fetched-entity updates.

Apply retrospective-guided updates to guidelines using h2 sql migrations, lombok super builder, and map struct mappers to update entities from dto, with not found handling in Spring MVC.

Master prompt engineering basics to improve results from agentic coding tools across platforms. Be specific, use delimiters and structured inputs like JSON, YAML, and markdown to guide goals and tasks.

Refactor prompts with prompt templates by creating an applied prompts folder and a templates directory, defining placeholders and variable syntax, and using an ignore file.

Build a reusable add query parameter template for Spring Boot with optional paging, service layer handling, and updated OpenAPI documentation and tests.

Live code a React-based front end for a Spring Boot project, using Vite, TypeScript, Radix, and Tailwind CSS, with a Maven build step and iterative debugging guided by Junie.

Leverage JetBrains AI and Junie to revise a requirements document, iterating prompts with Gemini to clarify dependencies, configuration needs, and build considerations for a React front end in vibe coding.

Develop a detailed implementation plan and a long task list using AI prompts and Gemini via JetBrains, then refine the plan and prepare for the React UI coding phase.

Use a task list to generate a React front end by guiding Genie through step-by-step prompts, handling context limits and quotas while producing extensive JavaScript and TypeScript code.

Apply vibe coding to fix React build errors by iterating with an AI tool, updating frontend guidelines, and running npm install, build, tests, and lint for a working project.

Run a Spring Boot and React project, troubleshoot build and display issues with Jouni, fix circular dependencies, adjust Tailwind and Radix styling, and verify a complete, styled front end.

Fork the repository, clone it locally, and use a master and per-lesson branch workflow to compare your work with the source and fetch updates from the original repository.

Demonstrates using the GitHub Copilot workspace to generate a RESTful CRUD API for the document categories table, including Flyway migration, JPA entity, DTO, MapStruct mapper, repository, service, controller, and tests.