AI-Augmented Software Development
Audience
This learning path is designed for professional software developers and engineering teams who are expected to use AI assisted coding tools while maintaining responsibility for code quality, security, and long-term maintainability.
It is ideal for developers, senior engineers, and technical leads who must integrate AI into real development workflows without lowering engineering standards.
Focus
This path is not about letting AI write code unchecked.
It focuses on helping developers understand how AI generated code is produced, where it can mislead, and how to evaluate it with the same rigor applied to human written code.
Participants learn how tools like GitHub Copilot influence design decisions, how AI changes testing and debugging practices, and where additional scrutiny is required. The path reinforces ownership of code and emphasizes the developer’s role in review, validation, and decision making.
The path also addresses how AI affects team workflows, code reviews, and long-term system health.
Outcomes
Developers use AI to accelerate development without sacrificing reliability, security, or maintainability.
They remain fully accountable for the code they ship, make more informed engineering decisions, and integrate AI into their workflows in ways that support quality today and resilience over time.
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