This is the fourth 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 3, we explored:
- How Generative AI tools could potentially upend the longstanding ratio of 5 engineers to 1 product manager.
- How tools like Github Copilot and AWS Amplify Studio could reshape product development, shifting the engineer’s focus from hand coding to design, architecture, and integration.
- How Generative AI tools can assist teams who are facing painfully outdated tech, handling complex porting and refactoring effortlessly.
- The possible unifying influence of AI tools on mobile and web app development, reducing duplicated efforts and bridging the skill gaps between web, Android, and iOS development.
- The impact of coding automation on junior developers and engineering progression
LLMs have changed the game and given us access to Generative AI — they can now at least give the impression of ‘applying expertise’ despite McKinsey’s predictions. Unlike the vapourware of the Metaverse and Web 3.0, there are big, meaningful opportunities for Generative AI tools to change the work that we do, and there will be winners and losers of this epochal shift.
Despite recent positive signs from the US economy and a gangbusting return to profitability from Microsoft, Google and Meta, inflation-linked timidity in the global economy will likely play a part in how people respond to this opportunity. If we were back in the boom years leading up to 2023, most companies would see the current situation as a growth opportunity, with an artificial fervour caused by the unhinged investment bubble and tech valuations of the last five years.
But we’re now in a different world. For those not tracking the parlous state of venture capital, funding in…