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AI-Assisted Software Development

Help engineering teams use AI coding tools productively without compromising quality.

Overview

Designed for people who already write software, this program covers how to integrate AI tools across the development lifecycle. It focuses on context, review discipline, testing, and team practices rather than on any single tool.

Who it is for

  • Software engineers
  • QA engineers
  • Technical leads and engineering managers

Learning objectives

  • Apply AI tools across the development lifecycle
  • Give AI tools the right context for a codebase
  • Review AI-generated code critically
  • Agree team practices for AI-assisted work

Topics and modules

  1. Module 1

    AI across the lifecycle

    • Requirements
    • Implementation
    • Testing and documentation
  2. Module 2

    Working in real codebases

    • Providing context
    • Planning changes
    • Refactoring safely
  3. Module 3

    Quality and security

    • Code review
    • Test generation
    • Security awareness
  4. Module 4

    Team adoption

    • Shared conventions
    • Measuring impact
    • Common pitfalls

Practical exercises

  • Implement a feature in an existing codebase with AI support
  • Review and correct flawed AI-generated code
  • Draft AI working agreements for a team

Expected learning outcomes

  • Use AI tools effectively on real engineering work
  • Maintain quality standards on AI-assisted changes
  • Propose a practical adoption approach for your team

Bring this program to your group

Each program can be shaped around your learners, their experience, and your goals.