fr
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Master AI-augmented coding with vibe coding and SDLC 2.0
AI assistants can support development, but you remain responsible for delivered code. Structure their use to prepare, examine and evolve your work. Develop a practice combining coding assistance, verification and control of the development lifecycle.
- Duration
- 4 days 28 hours
- Code
- DEV019FR Code
Presentation
Generative AI is radically transforming software engineering, shifting developers towards an orchestration role. This intensive 4-day course enables you to master augmented coding and integrate AI at every stage of the software development lifecycle (SDLC), from requirements analysis to deployment.
The programme introduces vibe coding: learn to generate, review and assemble professional code while supervising AI. Use leading tools such as Microsoft Copilot, Windsurf, Lovable and Google Antigravity, and explore Model Context Protocol (MCP) servers to connect models to real systems.
Beyond code generation, the course emphasises operational excellence through clean code, security, AI-augmented DevSecOps and prompt governance. Complete a project from scratch with AI-generated architecture, tests and a CI/CD pipeline, preparing you for SDLC 2.0.
Objectives
By the end of this course, you will be able to:
- understand generative AI's impact on software engineering and its integration into the SDLC;
- practise vibe coding to orchestrate code production and oversee technical quality;
- master assistance tools such as GitHub Copilot, Windsurf and MCP to accelerate development;
- apply clean code, security and governance best practices in an AI context;
- design and deploy a complete AI-augmented project, including tests and CI/CD pipelines.
Program
Day 1: Understanding the foundations and transforming the SDLC
- AI's impact on software engineering: assistance versus autonomous generation.
- Evolving from the traditional SDLC to an augmented model for requirements, design and testing.
- Expected benefits: velocity, security and reduced technical debt.
Hands-on exercises
- Generate user stories and acceptance criteria from an unclear requirement.
- Use AI to detect inconsistencies and generate a UML/C4 architecture diagram.
Day 2: Mastering vibe coding and advanced prompting
- The vibe coding concept: developers as orchestrators of intent.
- Developer prompting techniques for intent, technical implementation, auditing and testing.
- The complete methodology: definition, guided generation, review and assembly.
Hands-on exercises
- Generate a complete API with unit tests and QA scenarios.
- Perform automated refactoring and add error handling through AI.
Day 3: Automating development with MCP
- How Model Context Protocol servers work and their architecture.
- AI + MCP workflows: interacting with files, Git repositories and databases.
- Use cases: code analysis, automatic documentation and CI/CD pipelines.
Hands-on exercises
- Create and modify a real project through an MCP server.
- Generate and audit a complete CI/CD workflow and automate the changelog.
Day 4: Securing practices and completing the project
- Clean code in the AI era: enforcing style and documenting intent.
- Augmented DevSecOps: security scans and AI-supported technical debt reduction.
- Governance: prompt management, traceability and compliance.
Hands-on exercises
- Final project: design and develop a complete working mini-application, including architecture, code, tests, documentation and CI/CD, using vibe coding and the tools studied.
Audience
This course is intended for experienced technical professionals, including:
- experienced developers, Tech Leads and software architects evolving towards orchestration roles and mastering vibe coding;
- DevOps engineers and SREs integrating AI into CI/CD pipelines and automating infrastructure tasks;
- QA engineers and testers automating test and validation scenario generation;
- technical project managers understanding AI's impact on the software lifecycle to lead teams more effectively.
Prerequisites
The following prerequisites apply:
- Technical experience: proficiency in at least one modern programming language, such as JavaScript, Python or Java.
- Tools: knowledge of Git and development workflows, and familiarity with IDEs and terminals.
- Concepts: general understanding of the software development lifecycle.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Practical exercises
Course highlights
- Forward-looking methodology: adopt vibe coding and the developer-orchestrator role.
- Modern technology stack: use recent tools such as Windsurf, Lovable and MCP.
- DevSecOps approach: integrate security and clean code without sacrificing quality for speed.
- Complete project: build an augmented application from start to finish to demonstrate your new skills.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
Brand names and logos mentioned in this course description, such as Microsoft Copilot, GitHub, Windsurf and Lovable, belong to their respective owners.
Their use for educational purposes does not constitute a commitment or partnership.