Academia

Artificial intelligence – Introduction to AI to enhance software developmen

Artificial intelligence is transforming the way software is developed.This introductory course shows how to leverage AI in a practical and responsible way, integrating it into everyday code development, analysis, and review processes. A hands-on course on how to collaborate with AI to design architectures, generate code, debug, and improve software quality. During the workshop, we will analyze various tools and real-world use cases, from ChatGPT to Claude, from Cursor to Copilot, to show how AI can support developers at every stage of an application’s lifecycle: from planning to release. A pragmatic approach, designed for professionals, teachers, and team leaders who want to integrate artificial intelligence into their workflows without losing control, quality, and creativity.

Topics covered

AI-powered software development
Prompt Engineering in the software development cycle
AI Agents and IDE integrations
Assisted debugging and refactoring
Code review and code quality with AI
Ethics, control, and responsibility in the use of generative models

Program

1. Introduction: Beyond Vibe Coding

What is “vibe coding” and why does it pose a real risk to development teams?
AI as an amplification tool, not a replacement.

2. Planning and architecture with AI

How to define technology stacks and design patterns with the help of AI.
Architectural brainstorming and requirements analysis through the use of AI chatbots.

3. The virtuous cycle of AI-driven development

Generate → Test → Ask → Correct → Improve: the iterative flow with AI.
How to handle errors and guided debugging.
Refactor, documentation, and automatic code optimization.

4. From chat to action: integrated agents

IDE and Agents: Cursor, Junie, Claude Code.
How to safely delegate complex tasks (refactoring, testing, environment setup).

5. Code Review and Continuous Improvement

Automatic review tools.
Automate issue tracking and intelligent merge requests.
Integration into DevOps workflows and enterprise CI/CD processes.

6. Ethics and human oversight

How to maintain oversight of generated code.
Strategies for evaluating quality, security, and accountability.

Course

Artificial intelligence – Introduction to AI to enhance software developmen

Aimed at: Software Developers, Solution Architects, DevOps Engineers

Recommended prerequisites: Basic knowledge of software development (any language) Familiarity with Git, CI/CD, and modern IDEs

Duration: 4 hours

Course

Artificial intelligence – Introduction to AI to enhance software developmen

Aimed at: Software Developers, Solution Architects, DevOps Engineers

Recommended prerequisites: Basic knowledge of software development (any language) Familiarity with Git, CI/CD, and modern IDEs

Duration: 4 hours

Artificial intelligence – Introduction to AI to enhance software developmen

Artificial intelligence is transforming the way software is developed.This introductory course shows how to leverage AI in a practical and responsible way, integrating it into everyday code development, analysis, and review processes. A hands-on course on how to collaborate with AI to design architectures, generate code, debug, and improve software quality. During the workshop, we will analyze various tools and real-world use cases, from ChatGPT to Claude, from Cursor to Copilot, to show how AI can support developers at every stage of an application’s lifecycle: from planning to release. A pragmatic approach, designed for professionals, teachers, and team leaders who want to integrate artificial intelligence into their workflows without losing control, quality, and creativity.

Topics covered

AI-powered software development
Prompt Engineering in the software development cycle
AI Agents and IDE integrations
Assisted debugging and refactoring
Code review and code quality with AI
Ethics, control, and responsibility in the use of generative models

Program

1. Introduction: Beyond Vibe Coding

What is “vibe coding” and why does it pose a real risk to development teams?
AI as an amplification tool, not a replacement.

2. Planning and architecture with AI

How to define technology stacks and design patterns with the help of AI.
Architectural brainstorming and requirements analysis through the use of AI chatbots.

3. The virtuous cycle of AI-driven development

Generate → Test → Ask → Correct → Improve: the iterative flow with AI.
How to handle errors and guided debugging.
Refactor, documentation, and automatic code optimization.

4. From chat to action: integrated agents

IDE and Agents: Cursor, Junie, Claude Code.
How to safely delegate complex tasks (refactoring, testing, environment setup).

5. Code Review and Continuous Improvement

Automatic review tools.
Automate issue tracking and intelligent merge requests.
Integration into DevOps workflows and enterprise CI/CD processes.

6. Ethics and human oversight

How to maintain oversight of generated code.
Strategies for evaluating quality, security, and accountability.