Pods are the next step in an ongoing project management organization evolution. In recent decades, so-called scrum teams—cross-functional groups focused on deploying and iterating quickly—have replaced a slower, step-by-step project management methodology known as “waterfall,” which is noted in Chapter 3 of your Heizer/Render/Munson text.
Smaller than a traditional project management group, pods are designed to move faster to build. They are also more cross-functional, including engineers, designers and applied scientists. And critically, all that expertise is concentrated in just a handful of human workers (anywhere from 1 to 8), as well as AI agents.
For years project managers have been slowly favoring smaller and smaller teams in the name of speed and agility, but the growing capabilities of AI coding assistants and other agents that can potentially reduce time are allowing for even smaller pod-size structures. With AI agents doing more of the actual software development, including coding and testing, it takes fewer human workers to complete projects.
The benefit of pods is speed, agility and the ability to do more, faster, with fewer resources, said a Coinbase tech leader. That company now has a team of 3 people working on an AI adviser project, he said, adding that: “historically an undertaking like that would have required 10 to 15 people. There are these exponential gains when we have fewer people because you’re spending a lot less time in meetings and reviews and getting people on the same page.”
In the early days of Amazon, Jeff Bezos famously advocated for the idea of the “two-pizza team”—that is, any team should be small enough that it could be fed with two pizzas. “If you have a large team, you spend half your time just talking to each other and trying to figure out what needs to be done,” said Amazon’s VP.
Classroom discussion questions:
- How is AI influencing the management of large projects?
- What is an AI agent?
