GenAI & AI Agents for Java Spring Boot Devs | Copilot,Claude

Learn how machine learning trains models from data and what large language models are. See how AI interfaces like ChatGPT, Gemini, and Claude provide access to these models.

Master prompt engineering by turning vague instructions into detailed prompts with clear context and goals, enabling AI models to deliver accurate, high-quality outputs for coding and agents.

Explore how to craft perfect prompts for AI agents by using role, persona, context, clear instructions, positive framing, and output format; tailored for Java Spring Boot developers.

Master zero-shot prompting, instructing an AI to perform tasks without examples. Compare it to one-shot prompting and the need for examples in classification tasks to improve accuracy.

Explore many-shot prompting with large example sets to enhance AI agent precision in bug triage, using p0–p3 priorities, ample diverse seeds, and context window considerations.

Explore chain-of-thought prompting that forces AI to think step by step, providing auditable, thought-through reasoning for session storage decisions between Redis and PostgreSQL.

Explore cloud code, an agentic coding tool that reads your code base, understands context, and autonomously writes code, fixes bugs, and runs tests.

Learn to read a spring boot codebase with Claude Code AI Agent by cloning the repo, opening it in IntelliJ, and inspecting the rest controller.

Set up Claude code on your machine and in IntelliJ IDEA, install cloud code and Claude code plugin, configure path, authenticate with Anthropic, and use Claude code in JetBrains.

Install cloud code in Visual Studio Code and explore a context-aware chat interface with session history and mode options for planning, editing, and automation.

Discover Claude memory: runtime learning from coding patterns and a Claude.md project memory with instructions. Initialize and edit this file to steer Claude’s context, commands, and Lombok usage across sessions.

Launch and monitor parallel ai agent jobs in Claude Code by running background tasks in cloud code shells, viewing outputs, and switching between microservice shells.

Manage Claude sessions by creating multiple independent sessions for different tasks, then resume, rewind, or clear context to control memory and cost.

Learn to use Claude code agent with cloud code to add validations in the create post endpoint, manage file context, review diffs, and test changes.

Fix production bugs with Claude Code AI Agent in a Java Spring Boot app by validating post IDs, handling not-found responses, and improving word-count logic by converting strings to integers.

Learn ai powered refactoring with Claude Code to convert request parameters into a reusable post DTO, replace static state, and move validation into application properties for production-grade Spring Boot apps.

Apply token awareness and cost monitoring for Claude in ai agents by using context and cost commands, compact history, and clear to control tokens, context window, and subscription stats.

Create reusable cloud code skills with a skill.md file to automate instructions. Invoke personal or project level skills in cloud code to explain code with diagrams, architecture, and knowledge transfer.

stay in control when using ai agents and avoid overprompting by breaking tasks into stepwise workflows. review ai-generated code to preserve fundamentals, architecture, and scalable performance in production.

Explore Google's anti-gravity, an agentic development platform enabling autonomous agents to automate tasks. Learn about its desktop app, command line interface, integrated development environment, and software development kit.

Configure the antigravity IDE by cloning a repository, trusting the author, and installing the Java extension pack. Use the built-in AI agent with Gemini and Claude.

Experience ai-powered editor in antigravity that predicts and suggests code, refines variable names, adds validations, analyzes projects with an embedded agent, and enables chat-driven, in-context code edits.

Discover how antigravity skills turn repetitive instructions into reusable AI agent workflows in the IDE. Create workspace or global skills with skill.md, scripts, and resources to automate code review standards.

Explore GitHub Copilot, an agentic AI assistant embedded in your IDE, offering native GitHub integration, AI agents, autosuggest, and cross-platform support with token-based pricing and a free tier.

Install and sign in to GitHub Copilot in your IDEs by adding the official Copilot plugin, authenticating with GitHub, and optionally installing the CLI for terminal use.

Explore copilot cli in the terminal, log in to GitHub, and run commands to manage sessions and MCP server interactions, toggle instructions, and interact with agents.md and spring boot instructions.

Discover how Copilot in your IDE delivers inline and next-edit suggestions for real-time Java API development, including adding a put mapping to update a post with id, title, and content.

Explore how GitHub Copilot chat uses the current file context, reference other files via hash, and manage the context window, usage, and modes (agent and plan) in UI and CLI.

Explore end-to-end spring boot development with the Claude code ai agent. Turn post data into a post entity and update the controller for in-memory create, fetch, delete, and search.

Generate a layered Spring Boot setup by turning a Post class into a JPA entity, configuring H2, adding auditing, and creating a repository, service, and a clean controller.

Configure MCP servers in Visual Studio Code with GitHub Copilot, connect to databases like MySQL, PostgreSQL, SQL Server, SQLite, and MariaDB via DB hub MCP server, and run SQL queries.

Learn to configure a MySQL MCP server in Google Antigravity IDE to connect a local database, set up environment variables, and run SQL queries with AI-assisted guidance.

Configure GitHub MCP with Cloud Code or any AI assistant to interact with GitHub via natural language, generate template-backed commit messages, and push changes to the main repository.

Configure github mcp with cloud code to interact with github via AI tools and natural language, enabling AI-assisted commits and pushes with customizable commit message templates.

Explore MCP servers like context seven, GitHub, MySQL, PostgreSQL, Slack, and Playwright to modernize coding workflows. Fetch up-to-date docs, interact with databases, and automate tests.

Discover how AI agents autonomously plan, execute, and iterate toward end goals with memory, reasoning, and tool access, distinguishing agentic AI from traditional chatbots.

Build a pull request review agent that automatically reviews PRs and posts comments via a custom slash command, using cloud code, cloud MD, and a GitHub MCP server.