Building Software with AI: From Idea to Operations

A Practical Framework for Software Development in the Age of AI

How do we adapt organizations and teams for the changing economics of software development with generative AI?

This two-day workshop introduces a practical framework for discovering application and automation ideas, exploring those ideas with prototypes, validating those solutions, and then entering a continuous improvement process.

The course is technology-neutral, and not tied to one particular vendor or solution.

Throughout the workshop, participants work on a realistic case study based on a non-profit organization. With this case study, they take solutions from an initial business problem into an operating system.

Participants learn a five-stage lifecycle:

  • Discover — Understand the business problem, stakeholders, and opportunities.
  • Create — Rapidly prototype solutions using AI.
  • Verify — Evaluate solutions against criteria.
  • Operate — Use observability to monitor a running application, gather feedback, and learn from metrics. For the class, sample data is provided.
  • Improve — Continuously evolve software based on observed evidence and changing business needs.

This process helps businesses transform from thinking of internal software projects as shipped and finished, and instead considering them as continuously operating capabilities.

Who Should Attend

This workshop is designed for experienced professionals who work on software initiatives, not just software developers, including these titles:

  • Product Owners and Product Managers
  • Technical Program Managers
  • Business Analysts
  • Enterprise and Solution Architects
  • Innovation and Digital Transformation teams
  • Technical Consultants
  • Software Development Managers

No software development experience is required, although having participated in the software development process is going to help ground this process in real-world experience.

What You’ll Learn

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

  • Recognize software opportunities that AI makes practical to explore.
  • Move from business ideas to working software prototypes
  • Evaluate AI-generated software for quality and security.
  • Apply a practical lifecycle for discovering, creating, verifying, operating, and improving software.

This course is not about replacing Agile, Scrum, or existing software engineering practices.

The goal is to understand how teams and organizations can adapt their practices to the new world of AI-assisted software development.