Course Outline
Comprehending Tools and Initial Construction
Mechanics of AI Coding Tools
Key topics include:
• Grasping context windows and their inherent constraints
• The concept of statelessness and how AI models manage information within a session
• The Plan → Execute → Review methodology
• Identifying tasks where AI coding tools excel and areas where they may falter
• Strategies for effective collaboration with AI assistants
The Current AI Coding Ecosystem
Key topics include:
• An overview of the prevailing AI coding landscape
• Distinguishing between platforms like Cursor, GitHub Copilot, and Claude Code
• Choosing the optimal model and tool for specific requirements
• Evaluating the strengths and constraints of various coding assistants
• Practical guidance for adopting tools within development teams
Prompt Structure and Design
Key topics include:
• Essential elements of a high-quality prompt
• Providing clear context and precise task definitions
• Defining output formats and necessary constraints
• Utilizing established prompting frameworks and templates
• Methods to enhance prompt consistency and quality
Initial Coding: Development from Zero
Key topics include:
• Constructing a project starting from an empty directory
• Establishing the initial application structure and scaffolding
• Handling dependencies and project configuration
• Iteratively refining generated code
• Testing and polishing the final solution
Existing Codebases, Customization, and Audit
Integration with Existing Code
Key topics include:
• Exploring and understanding unfamiliar codebases
• Leveraging AI tools to query and analyze existing projects
• Mapping application architecture and dependency chains
• Generating technical documentation and summaries
• Streamlining the onboarding process for existing projects
Routine Activities: Debugging, Features, and Testing
Key topics include:
• Utilizing AI tools to diagnose and resolve bugs
• Developing new features and enhancements
• Authoring and improving automated tests
• Verifying generated code and modifications
• Boosting productivity in daily development tasks
Customization: Core Concepts
Key topics include:
• Understanding project rules and configuration files
• Introduction to AGENTS.md and project memory principles
• Identifying where and when customization mechanisms are applicable
• Best practices for configuring AI assistants
• Overview of advanced implementation strategies
Guardrails, Risks, and Professional Judgment
Key topics include:
• Auditing and validating AI-generated code
• Understanding typical failure patterns and limitations
• Identifying prompt injection and security vulnerabilities
• Determining which tasks are suitable for AI delegation
• Exercising human judgment and maintaining accountability in software development
Requirements
Participants do not need prior experience with coding or AI tools.
While not mandatory, a basic understanding of code or Git is advantageous
A licensed account for Claude Code, Cursor, or Copilot
Intended Audience:
Individuals new to AI-assisted development, including non-coders, intermittent coders, and professionals in technical-adjacent roles such as QA, data, product, or operations. No prior development background is presumed.
Testimonials (3)
start to use AI with purpose
Alessandro - IC Outsourcing
Course - Claude AI - Fast Track Session
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.
