Course Outline
Day 1 | Understanding the Tools and Building Your First Project
Module 1 | How AI Coding Tools Actually Work
Covered topics:
• Understanding context windows and their limitations
• Statelessness and how AI models retain information during a session
• The Plan → Execute → Review workflow
• Capabilities of AI coding tools and areas where they struggle
• Best practices for effective collaboration with AI assistants
Module 2 | The AI Coding Landscape
Covered topics:
• Overview of the current AI coding ecosystem
• Key differences between tools like Cursor, GitHub Copilot, and Claude Code
• Selecting the appropriate model and tool for specific tasks
• Strengths and limitations of various coding assistants
• Practical recommendations for adopting tools within development teams
Module 3 | The Anatomy of a Prompt
Covered topics:
• Essential components of an effective prompt
• Providing context and defining tasks clearly
• Specifying output formats and constraints
• Common prompting frameworks and templates
• Techniques for improving prompt quality and consistency
Module 4 | First Coding: Building from Scratch
Covered topics:
• Creating a project in an empty folder
• Establishing the initial application structure and scaffolding
• Managing dependencies and project configuration
• Iteratively refining generated code
• Testing and polishing the final solution
Day 2 | Working with Existing Codebases, Personalization, and Review
Module 5 | Working Within a Codebase
Covered topics:
• Navigating and comprehending an unfamiliar codebase
• Querying and analyzing existing projects using AI tools
• Mapping application structure and dependencies
• Generating documentation and technical summaries
• Accelerating onboarding into ongoing projects
Module 6 | Everyday Tasks: Debugging, Features, and Testing
Covered topics:
• Using AI tools to investigate and resolve bugs
• Implementing new features and enhancements
• Writing and improving automated tests
• Validating generated code and changes
• Boosting productivity in day-to-day development tasks
Module 7 | Personalization: Concepts and Application
Covered topics:
• Understanding project rules and configuration files
• Introduction to AGENTS.md and project memory concepts
• Where and when personalization mechanisms apply
• Best practices for configuring AI assistants
• Overview of advanced implementation approaches
Module 8 | Guardrails, Risks, and Judgment
Covered topics:
• Reviewing and validating AI-generated code
• Understanding common failure modes and limitations
• Recognizing prompt injection and security risks
• Determining which tasks can be delegated to AI
• Applying human judgment and maintaining accountability in software development
Requirements
No prior coding experience or familiarity with AI tools is required.
Basic knowledge of code or Git is beneficial.
A licensed account for Claude Code, Cursor, or Copilot is needed.
Audience:
This course is designed for those new to AI-assisted development, including non-coders, occasional programmers, and professionals in technical-adjacent roles such as QA, data analysis, product management, or operations. No prior development background is assumed.
Testimonials (2)
Using Claude Code in a more efficient way
Virgil Trif - Frequentis
Course - Claude Code: Agentic AI Development · 1-Day
"I learned the potential of the tool and gained sufficient skills to start using it for my work right away
