Across developer and product management communities, there is growing discussion and interest around the impact of AI on product roles. Industry experts are exploring how AI is “redefining the product manager’s role” and the need for “AI-native” product teams.
The core challenge is that AI is making it easier than ever to ship polished, functional products — but that also makes it harder for individual offerings to truly stand out. “Anyone can integrate a chatbot or image generator now,” notes Elijah Gwynne, founder of AI product consultancy Cogent. “The real differentiation comes from how you leverage your unique data, domain expertise, and workflows to build something truly custom and valuable.”
Several frameworks, playbooks, and tools are emerging to help product teams do just that. Gwynne’s team, for example, has developed a structured process to help founders and product managers inventory their company’s unique assets — from the data they’ve collected to the processes their team has honed over years. “The goal is to find those idiosyncratic advantages and translate them into AI-powered features that competitors can’t easily replicate,” he explains.
One such example is Adept, an AI system designed to learn and execute arbitrary tasks by interacting with applications and websites. Rather than building a generic language model, the Adept team leveraged their deep understanding of software automation to create an AI that can fluidly navigate digital interfaces. “The big innovation isn’t the language model itself,” says Adept co-founder Daniel Ziegler, “it’s how we trained it to become an expert ‘digital assistant’ that can actually get work done, not just chat.”