Course Outline
Tool Fundamentals and Initial Construction
Insights into AI Coding Tool Mechanisms
Key topics include:
• Grasping context windows and their inherent constraints
• The concept of statelessness and how AI models handle information retention during a session
• The Plan → Execute → Review workflow
• Identifying areas where AI coding tools excel and where they face challenges
• Optimal strategies for effective collaboration with AI assistants
The AI Coding Ecosystem
Key topics include:
• A broad overview of the contemporary AI coding landscape
• Distinguishing the features of tools like Cursor, GitHub Copilot, and Claude Code
• Choosing the appropriate model and tool for specific tasks
• Evaluating the strengths and limitations of different coding assistants
• Practical advice for integrating tools within development teams
Anatomy of Prompts
Key topics include:
• Essential elements of a high-quality prompt
• Clear context provision and task definition
• Defining output formats and constraints
• Common prompting frameworks and templates
• Methods for enhancing prompt quality and consistency
Initial Coding: Construction from Zero
Key topics include:
• Developing a project starting from an empty directory
• Establishing the initial application structure and scaffolding
• Managing dependencies and project settings
• Refining generated code through iteration
• Testing and polishing the final solution
Navigating Existing Codebases, Customization, and Review
Interacting with Existing Codebases
Key topics include:
• Navigating and comprehending unfamiliar codebases
• Using AI tools to query and analyze existing projects
• Mapping application architecture and dependencies
• Creating documentation and technical overviews
• Streamlining onboarding for new projects
Routine Tasks: Debugging, Feature Addition, and Testing
Key topics include:
• Leveraging AI tools to diagnose and resolve bugs
• Developing new features and improvements
• Creating and optimizing automated tests
• Verifying generated code and modifications
• Enhancing efficiency in daily development activities
Customization: An Overview
Key topics include:
• Understanding project rules and configuration files
• Introduction to AGENTS.md and project memory concepts
• Application scenarios for personalization mechanisms
• Best practices for setting up AI assistants
• Overview of advanced implementation methods
Guardrails, Risks, and Decision-Making
Key topics include:
• Reviewing and validating AI-generated code
• Understanding common failure modes and constraints
• Identifying prompt injection and security threats
• Determining which tasks are suitable for AI delegation
• Exercising human judgment and maintaining accountability in software development
Requirements
No previous experience with coding or AI tools is necessary.
Basic knowledge of code or Git is beneficial
Licensed account for Claude Code / Cursor / Copilot
Target Audience:
Individuals new to AI-assisted development, including non-coders, occasional programmers, and roles adjacent to technology in 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.
