Modern AI-Native Software Engineering with Java, Claude Code

Build Modern Software with AI-Native Engineering Workflows

AI is fundamentally changing how software engineers build and deliver software. The opportunity is not just to use AI for coding. It is to engineer a development workflow where AI can dramatically accelerate implementation while you remain in control of the architecture and engineering decisions.

Take your software engineering skills to the next level by learning how to build high-quality distributed systems faster with AI.

In this hands-on course, you will use Claude as an AI development partner to design, analyze, plan, implement, test, review, and deliver software through a structured engineering workflow.

You will learn how to:

• Build an AI-driven software engineering workflow from task specification to pull request

• Use Context Engineering, project rules, and CLAUDE md to give AI the right engineering context

• Create reusable Skills to automate development activities

• Integrate AI with GitHub to streamline the development lifecycle

• Use Subagents to parallelize development and delegate specialized engineering tasks

• Build workflows using Planner, Implementer, and Coder subagents

• Improve implementation quality through structured planning and code review

• Connect AI to external systems using Model Context Protocol (MCP)

• Use PostgreSQL through MCP

The goal is simple: build better software, faster.

By the end of the course, you will understand how to combine your Java/Spring Boot expertise with modern AI capabilities to build sophisticated distributed systems while automating and accelerating significant parts of the engineering workflow.

This is the next step in becoming a modern software engineer who knows how to leverage AI effectively.