AI-Assisted Software Development: Practical Tools and Workflows
About This Course
The era of relying solely on standard auto-complete in your code editor is over. To achieve maximum productivity, modern developers are moving straight to the terminal, leveraging powerful Agentic Command Line Interface (CLI) tools like Claude Code and Codex. This is a highly practical, hands-on course designed to fundamentally upgrade your daily development loop.
In this two-day course, you will learn how to integrate command-line AI agents directly into your repository. We will guide you through the complete feature lifecycle: starting with how to effectively create a robust Product Requirements Document (PRD) from raw business needs, and then teaching you how to translate that PRD into the precise, structured context an AI needs to autonomously scaffold full-stack applications. You will move beyond simple code snippets to commanding your CLI agent to perform multi-file feature additions, deep legacy code refactoring, and terminal-based debugging.
Crucially, speed without guardrails creates technical debt. Therefore, you will also learn how to prompt AI agents to write comprehensive end-to-end tests (using Playwright) and how to identify and patch the subtle security vulnerabilities commonly introduced during AI code generation (the “Vibe Coding Trap”). You will leave this course ready to build, test, and ship software at an unprecedented velocity.
What You'll Learn
• Navigate and command Agentic Command Line Interface (CLI) tools (such as Claude Code or Codex) to execute multi-file edits, refactors, and codebase scaffolding directly from the terminal.
• Create robust Product Requirements Documents (PRDs) and systematically deconstruct them into highly structured technical specifications that guide artificial Intelligence (AI) agents accurately.
• Debug complex software issues by seamlessly feeding terminal error logs and stack traces back into CLI agents for immediate resolution.
• Automate software quality assurance by instructing AI agents to generate comprehensive unit tests and robust Playwright end-to-end (E2E) tests.
• Identify and mitigate AI-generated technical debt and security vulnerabilities by applying systematic code auditing and human-in-the-loop validation strategies.
Entry Requirements
General Diploma