Description
This training explores how artificial intelligence can be integrated into modern software development practices beyond simple code generation. Participants learn how to work with AI tools to support writing, refactoring, debugging and documenting code, while maintaining strong software engineering standards.
A core focus of the training is validation: understanding how to assess, test and verify AI-generated code. Participants revisit key software engineering concepts—such as specifications, architecture, testing strategies and code review—that are essential to safely adopting AI-first programming approaches.
The training introduces emerging practices such as spec-driven programming, AI-first development workflows, and the role of infrastructure components such as MCP servers, while emphasizing critical judgment, security and long-term maintainability.
This training is designed for technical audiences and assumes prior programming experience.
Objectives
At the end of the training, participants will be able to:
- integrate AI tools into their coding workflow while preserving engineering rigor
- validate, test and critically assess AI-generated code
- apply spec-driven and AI-first programming principles
- identify limitations, risks and failure modes of AI-assisted development
- adopt secure, maintainable and responsible coding practices when working with AI
For whom
This training is intended for:
- students or professionals with coding experience
- software developers
- programmers and engineers
- technical and IT teams
Format and delivery
- in-person, remote or hybrid delivery
- flexible duration (workshop, half-day, full day)
- adaptable to programming languages and context