Generative AI for Software Engineering Teams: Modern Developer Workflows

The software engineering landscape is evolving rapidly with the rise of artificial intelligence. Teams that successfully integrate generative AI into their daily workflows write better code faster, reduce manual overhead, and focus on solving high-level architectural problems. This text-based course equips you with the foundational knowledge and practical strategies needed to adopt Generative AI (GenAI) tools within a software engineering team. You will discover how to transition from manual coding patterns to AI-assisted development workflows without sacrificing code quality or security. What you'll learn: - Understand the core terminology, capabilities, and limitations of large language models in software development - Apply effective prompt engineering techniques specifically tailored for generating, refactoring, and documenting code - Leverage AI tools to automate unit testing, generate mock data, and assist in code reviews - Integrate retrieval-augmented generation (RAG) concepts to help AI understand your private codebase context - Address security, privacy, and intellectual property considerations when using AI assistants - Establish team-wide best practices for collaborative AI-driven development You will begin by learning fundamental AI concepts and terminology before exploring practical, step-by-step written guides on prompt structures, testing workflows, and codebase context management. This course is designed for software engineers, tech leads, and product managers who are new to GenAI and want to introduce these tools into their development process. No prior AI experience is required. Start reading today to modernize your software engineering workflow and lead your team into the future of development.