Course Outline
Day 1 | Grasping Tool Mechanics and Initial Build
Module 1 | The Inner workings of AI Coding Tools
Key topics:
• Context windows and their inherent constraints
• The concept of statelessness and information retention during sessions
• The Plan → Execute → Review workflow
• Capabilities and limitations of AI coding tools
• Best practices for effective collaboration with AI assistants
Module 2 | The Current AI Coding Landscape
Key topics:
• An overview of the contemporary AI coding ecosystem
• Differentiating between tools like Cursor, GitHub Copilot, and Claude Code
• Selecting appropriate models and tools for specific tasks
• Strengths and weaknesses of various coding assistants
• Practical advice for adopting tools within development teams
Module 3 | Deconstructing Prompts
Key topics:
• Essential elements of a high-quality prompt
• Context provision and clear task definition
• Defining output formats and boundary conditions
• Standard prompting frameworks and templates
• Methods to enhance prompt precision and reliability
Module 4 | Initial Coding: Building from Zero
Key topics:
• Initiating a project from an empty directory
• Establishing initial application structure and scaffolding
• Handling dependencies and project settings
• Iteratively refining generated code
• Testing and polishing the final solution
Day 2 | Working with Existing Code, Customization, and Review
Module 5 | Navigating an Existing Codebase
Key topics:
• Interpreting and exploring unfamiliar codebases
• Utilizing AI tools to query and analyze existing projects
• Mapping application architecture and dependencies
• Generating documentation and technical overviews
• Streamlining the onboarding process for new team members
Module 6 | Routine Tasks: Bug Fixes, Features, and Testing
Key topics:
• Leveraging AI to diagnose and resolve bugs
• Developing new features and enhancements
• Creating and optimizing automated tests
• Verifying generated code and modifications
• Boosting productivity in daily development activities
Module 7 | Personalization: Core Concepts
Key topics:
• Interpreting project rules and configuration files
• Introduction to AGENTS.md and project memory mechanisms
• Scenarios where personalization features are applicable
• Best practices for setting up AI assistants
• An overview of advanced implementation strategies
Module 8 | Guardrails, Risks, and Critical Judgment
Key topics:
• Assessing 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 oversight and maintaining accountability in development
Requirements
No previous experience with coding or AI tools is necessary.
A basic understanding of code or Git is beneficial.
A licensed account for Claude Code, Cursor, or Copilot.
Target Audience:
Individuals new to AI-assisted development, including non-developers, casual coders, and professionals in adjacent technical fields such as QA, data, product management, or operations. No prior development background is expected.
Testimonials (2)
Learning how to prompt Claude and use it to digest all of the data I have available.
Mike Hartleroad - Furniture Row
Course - Claude AI for Data Analysis and Business Intelligence
how to engage with the Office environment and set up repetitive tasks
