AI-Native Engineering Workflow

Build high-quality, maintainable software solutions by applying Agentic AI to requirements, implementation, and testing.

Description

Generative AI offers tremendous opportunities to accelerate software development, but effectively leveraging it requires a structured approach. In this training, you will learn how to integrate Agentic AI into your development workflow, from generating requirements to implementing code and automating tests. You will discover how to use AI to deliver value quickly, while simultaneously ensuring the quality and maintainability of your code.

You will learn to:

• apply context engineering to provide AI with the right information and guidelines
• design, test, and deploy agents to automate specific tasks
• use agent orchestrations to enable multiple agents to collaborate
• develop skills to create reusable AI functionalities
• apply new techniques for reviewing generated code and ensuring consistency and quality

During the training, you will gain hands-on experience with Agentic AI by working on a project from the initial idea to working functionality. You will practice creating agents and skills, and apply them in a complete development process, from "a feature title" to an accepted pull request.

Note: This training focuses on building new features. For modernizing an existing codebase, see our Code Modernization Using Agentic AI training.

Learning Goals

• Complete a software development workflow using agentic AI, from feature title to validated implementation [Apply]
• Explain the difference between prompt engineering and context engineering [Understand]
• Write agents and agent orchestrations [Apply]
• Implement Skills and use them in agents [Apply]
• Explain the difference between instructions, prompts, agents, and skills [Understand]

Subjects

1. Workflow Overview
2. Context Engineering
3. Agents
4. Agentic Refinement
5. Agent Orchestrations
6. Skills
7. Test Agents
8. Generated Code Review
9. Workflow in my Team