Course Outline
Tool Overview and Initial Build
The Mechanics Behind AI Coding Tools
Key topics:
\u2022 Grasping context windows and understanding their constraints
\u2022 Statelessness and how AI models handle information within a session
\u2022 The Plan \u2192 Execute \u2192 Review process
\u2022 Identifying strengths and weaknesses of AI coding tools
\u2022 Strategies for effective collaboration with AI assistants
The AI Coding Ecosystem
Key topics:
\u2022 An overview of the current landscape of AI coding solutions
\u2022 Distinguishing between tools like Cursor, GitHub Copilot, and Claude Code
\u2022 Choosing the appropriate model and tool for specific tasks
\u2022 Evaluating the pros and cons of various coding assistants
\u2022 Practical advice for integrating these tools into development teams
Anatomy of a Prompt
Key topics:
\u2022 Essential elements of a high-quality prompt
\u2022 Clearly providing context and defining the objective
\u2022 Specifying desired output formats and constraints
\u2022 Exploring common prompting frameworks and templates
\u2022 Methods for enhancing prompt quality and consistency
Initial Coding: Building from Zero
Key topics:
\u2022 Creating a project starting from an empty directory
\u2022 Setting up the initial application structure and scaffolding
\u2022 Handling dependencies and project configuration
\u2022 Iteratively refining generated code
\u2022 Testing and polishing the final solution
Existing Codebases, Customization, and Review
Navigating an Existing Codebase
Key topics:
\u2022 Exploring and comprehending unfamiliar codebases
\u2022 Querying and analyzing existing projects with AI assistance
\u2022 Mapping out application structure and dependencies
\u2022 Generating documentation and technical summaries
\u2022 Speeding up onboarding into established projects
Daily Tasks: Fixing, Features, and Testing
Key topics:
\u2022 Leveraging AI tools to debug and resolve issues
\u2022 Implementing new features and improvements
\u2022 Writing and enhancing automated tests
\u2022 Verifying AI-generated code and changes
\u2022 Boosting productivity in routine development activities
Personalization: The Basics
Key topics:
\u2022 Understanding project rules and configuration files
\u2022 Introduction to AGENTS.md and the concept of project memory
\u2022 Identifying where and when personalization features apply
\u2022 Best practices for configuring AI assistants
\u2022 Overview of advanced implementation methods
Guardrails, Risks, and Judgment
Key topics:
\u2022 Reviewing and validating code generated by AI
\u2022 Understanding common failure modes and limitations
\u2022 Recognizing prompt injection threats and security risks
\u2022 Determining which tasks are suitable for AI delegation
\u2022 Applying human judgment and maintaining accountability in software development
Requirements
No prior coding experience or familiarity with AI tools is necessary.
Basic knowledge of code or Git is advantageous
A licensed account (for Claude Code / Cursor / Copilot)
Target Audience:
This course is designed for individuals new to AI-assisted development, including non-coders, occasional developers, and professionals in adjacent technical fields such as QA, data, product, or operations. No prior development background is assumed.
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.
