Practical course on how software engineering is evolving in the AI era — from AI-assisted workflows to AI-native development practices, engineering processes, and future-ready teams.
Who Is the AI Native Course For?
- Senior Software Engineers
- Team Leads and Tech Leads
- Solution Architects
- Engineering Managers
- CTOs and technical decision-makers
- Product-minded developers
- Engineering teams preparing for AI transformation
- Technical specialists adapting to AI-first development environments
What You Will Learn
- Build AI-native engineering workflows
- Integrate AI across the software development lifecycle
- Combine human expertise with AI capabilities effectively
- Use AI for architecture, development, QA, documentation, and delivery
- Design engineering processes with AI in mind
- Improve engineering productivity through AI-native practices
- Understand AI limitations, risks, and governance principles
- Adapt engineering skills and career paths to the AI era
Course Program
Module 1
THE SHIFT TO AI-NATIVE ENGINEERING
Topic 1.1. How AI is transforming software engineering
- AI-native vs traditional engineering
- Evolution of software development workflows
- AI-first product development
- The changing role of engineers
Topic 1.2. AI-native ecosystem for engineers
- Modern AI development tools
- AI-powered IDEs and copilots
- AI-assisted engineering environments
- Emerging AI-native workflows
Module 2
AI-NATIVE DEVELOPMENT WORKFLOWS
Topic 2.1. AI across the Software Development Lifecycle
- AI in planning and requirements
- AI in architecture and design
- AI in coding and refactoring
- AI in testing and QA
- AI in delivery and maintenance
Topic 2.2. AI-assisted engineering execution
- Context-aware prompting
- Working with large codebases
- AI pair engineering
- Productivity optimization with AI
Module 3
HUMAN + AI COLLABORATION
Topic 3.1. Effective collaboration with AI
- Human + AI workflows
- Prompt systems for engineers
- Context management
- AI-supported decision-making
Topic 3.2. AI limitations, risks & governance
- Responsible AI usage
- Security considerations
- Risks of overreliance on AI
- AI governance principles for engineering teams
Module 4
FUTURE OF ENGINEERING
Topic 4.1. AI-native teams & organizations
- AI-native engineering culture
- New engineering roles
- AI-driven productivity models
- Future engineering organizations
Topic 4.2. Future-proof engineering careers
- Skills for the AI era
- Career adaptation strategies
- Continuous learning in AI-native environments
- The future of software engineering
AFTER COURSE COMPLETION
Students will gain practical competencies in:
- AI-native engineering workflows
- AI-first software development practices
- Human + AI collaboration models
- AI-supported architecture and delivery
- Engineering productivity optimization
- AI governance and responsible AI usage
- Modern AI tooling for engineering teams
- Future-ready engineering practices
REQUIRED BACKGROUND
- Strong understanding of software development processes
- Experience working in engineering teams
- Understanding of software architecture and workflows
- Technical background is recommended
- Basic familiarity with AI tools will be an advantage
Advanced
Middle
*If you have a personal discount promo code, please enter it in the comment field of the registration form.
Payment in installments without commission and interest is available from PrivatBank
In case of any questions, please contact the manager Sofiia
