This is the third part of a six part series investigating how generative AI productivity tools aimed at developers, like Github Copilot, ChatGPT and Amazon CodeWhisperer might impact the structure of entire product engineering teams.
In Part 2, we explored:
- How generative AI tools like ChatGPT are redefining the way product engineering teams approach coding — from generating user stories to writing the actual code.
- How tasks often perceived as tedious by developers, like writing tests and documentation, can now be easily and efficiently handled by AI, making the entire coding process more streamlined.
- The crucial importance of tests and the potential future of prompt-engineered applications that might be initiated with thoughtful test design.
- A vision of the future where Generative AI tools reshape the roles within product engineering teams and the profound implications for engineers and leaders.
The idea that I’ve been consumed with for the past few months is that the impact of Generative AI tools on product engineering teams is going to cause a fundamental shift in the ratio of product to technical roles. In part one of this series, I reflected that a common ratio for engineers to product managers in many product teams was five engineers to one product manager.
Now, when I’m feeling either particularly bold or particularly fatalist, that hypothesis becomes:
“Current product engineering teams require five engineers to one product manager. Next-gen product engineering teams will require only one senior engineer for each product manager’
This is what I’d like to put to the test.
In the previous articles in this series we’ve discussed the individual impact of these developer and productivity tools, but I’d now like to pull your gaze back to a more strategic view — the impact that enhanced developer productivity will have on a team, and even…