Course Outline
Understanding the Tools and a First Build
How AI Coding Tools Actually Work
Key topics include:
• Grasping context windows and understanding their specific limitations
• Exploring statelessness and how AI models maintain information throughout a session
• Mastering the Plan → Execute → Review workflow
• Identifying the strengths of AI coding tools and recognizing their common challenges
• Adopting best practices for effective collaboration with AI assistants
The AI Coding Landscape
Key topics include:
• An overview of the current AI coding ecosystem
• Distinguishing between different tools such as Cursor, GitHub Copilot, and Claude Code
• Choosing the appropriate model and tool for specific tasks
• Analyzing the strengths and limitations of various coding assistants
• Practical recommendations for adopting these tools within development teams
Prompt Anatomy
Key topics include:
• Identifying the essential components of a high-quality prompt
• Effectively providing context and clearly defining tasks
• Defining output formats and setting necessary constraints
• Utilizing common prompting frameworks and templates
• Employing techniques to enhance prompt quality and consistency
First Coding: Build From Scratch
Key topics include:
• Constructing a project from an empty folder
• Establishing the initial application structure and scaffolding
• Managing dependencies and configuring the project
• Refining generated code through iterative processes
• Testing and polishing the final solution
Existing Codebases, Personalisation and Review
Working in a Codebase
Key topics include:
• Navigating and comprehending unfamiliar codebases
• Querying and analyzing existing projects with AI tools
• Mapping out application structures and dependencies
• Generating documentation and technical summaries
• Speeding up the onboarding process for existing projects
Everyday Tasks: Fix, Feature and Test
Key topics include:
• Leveraging AI tools to investigate and resolve bugs
• Implementing new features and system enhancements
• Writing and refining automated tests
• Validating generated code and verifying changes
• Boosting productivity in routine development tasks
Personalisation: What It Is
Key topics include:
• Understanding project rules and configuration files
• Introduction to AGENTS.md and the concept of project memory
• Identifying where and when personalisation mechanisms are applicable
• Following best practices for configuring AI assistants
• Getting an overview of advanced implementation strategies
Guardrails, Risks and Judgement
Key topics include:
• Reviewing and validating code generated by AI
• Understanding common failure modes and inherent limitations
• Recognizing prompt injection attacks and other security risks
• Determining which tasks are suitable for delegation to AI
• Applying human judgement and maintaining accountability in software development
Requirements
No prior coding or AI tool experience is necessary.
Basic familiarity with code or Git is beneficial
A licensed account for Claude Code, Cursor, or Copilot
Audience:
This course targets individuals new to AI-assisted development, including non-coders, occasional developers, and professionals in technical-adjacent roles such as QA, data, product, or operations. No background in software development is assumed.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
Contact us for an exact quote and to hear our latest promotions
Testimonials (2)
Considerations about privacy and policy
Angelo Stefano Soglia - Parkino srl
Course - Claude AI for Workflow Automation and Productivity
Learning how to prompt Claude and use it to digest all of the data I have available.
