Generative AI for Back End Developers

Practical Engineering with Agentic AI for Developers with Existing Systems

This two-day workshop covers agentic AI tools for working on existing business applications. Instead of building several brand new applications from scratch, this workshop is organized around understanding and migrating an existing example application.

The example project is a realistic legacy code base, and participants will get hands-on experience working within that context for every lab project.

The principles in this class are technology-neutral. The workshop can adapt to most agentic AI tools and frontier models. The practices learned during the class (web application security, testing, code reviewing, deployment) are generally technology-agnostic. The standard language for the examples and the legacy application is JavaScript, but should be understandable by most software developers.

Topics covered:

  • Working effectively with agentic AI
  • Understanding legacy systems with agentic AI
  • Relational databases and migrations with LLMS
  • Code reviews with AI tools
  • Testing with Playwright and agentic AI
  • Web application security
  • Deployment

Who Should Attend

This workshop is designed for professional back end developers, including:

  • Back end and full-stack software engineers
  • Senior engineers and tech leads
  • Developers responsible for maintaining or modernizing legacy systems

Participants should have roughly two or more years of professional development experience and be comfortable reading and writing code. Examples and labs use JavaScript/TypeScript, but deep expertise in it is not required.

What You’ll Learn

By the end of the workshop, participants will be able to:

  • Direct agentic AI tools productively on large, unfamiliar codebases
  • Use AI to build an accurate mental model of a legacy system
  • Evolve a production relational database safely with AI assistance for migrations
  • Run effective LLM-assisted code reviews
  • Build a Playwright-based testing harness
  • Find, prioritize, and fix common web application vulnerabilities with AI
  • Modernize a deployment path incrementally

This course is not a general AI learning class that teaches prompt engineering and specific agentic AI configurations and skills. Instead, it is a class that will help amplify existing engineering effort with LLM-based tools in an AI-forward, technology-neutral format.