In a recent LinkedIn post, Sachin Rekhi explores the profound ways Artificial Intelligence is reshaping the traditional product operating model. Rekhi, a prominent voice in the product development space, highlights five key transformations he is observing across product teams as they integrate AI into their workflows.
Shifting from Specs to Prototypes
One of the most significant shifts Rekhi identifies is the move from detailed product specifications to interactive prototypes. He argues that this approach offers distinct advantages in the age of AI-powered development.
“I’m seeing teams move away from spending weeks putting together detailed product specs and instead moving towards spending that same time refining prototypes. These are far less lossy than specs, easier to get customer feedback on, and quicker to explore multiple design directions.”
As Rekhi points out, prototypes facilitate a more dynamic and customer-centric development cycle. This aligns with the broader trend of rapid iteration, which AI is accelerating.
Customer Previews Trump Traditional Reviews
Rekhi also notes a departure from lengthy internal product and design review processes. Instead, teams are prioritizing direct customer feedback on early-stage prototypes.
“Teams are moving away from spending a lot of time up-front on product and design reviews and instead building prototypes quickly, putting them in front of customers, and then iterating from there.”
According to Rekhi, this method ensures that product development is guided by validated customer needs rather than internal assumptions. The reduced cost of creating and discarding prototypes further supports this agile approach, as Rekhi explains, “it’s fine when prototypes get thrown away due to poor customer feedback.”
The Blurring of Roles and Rise of Agent Managers
Another key observation from Rekhi concerns the evolving nature of team roles. He sees a trend towards the blending of traditionally siloed roles, enabled by AI tools.
Blending of Roles
Rekhi suggests that AI empowers individuals beyond traditional engineering roles to contribute to code. For instance, designers or product managers can now make minor UI or copy adjustments directly, leading to a more polished user experience without the overhead of traditional ticket systems. “Now, I’m not suggesting designers & PMs should be doing real engineering work, but these small fixes can now easily be handled by non-engineers, resulting in a far more polished product experience,” Rekhi writes.
Agent Managers Over Specialists
Furthermore, Rekhi highlights a shift from specialists performing tasks directly to them building AI agents that empower others. Roles like data analysts, researchers, and designers are increasingly focused on creating tools that product builders can leverage for analysis, research, and design.
“This significantly speeds up product builders and gives them far more leverage. But it also means the value of these specialists isn’t disappearing.”
In Rekhi’s view, this transformation allows specialists to amplify their impact by enabling broader team capabilities.
Adapting to Shorter Planning Horizons
Finally, Rekhi addresses the impact of AI on strategic planning. He observes a move towards shorter-term roadmaps, typically spanning six months, rather than multi-year plans.
This shift, according to Rekhi, is driven by two primary factors: AI’s ability to accelerate development cycles and the rapid pace at which AI itself is changing what is possible to build. This necessitates a more agile and responsive planning approach.
Rekhi concludes by inviting further discussion, asking about other AI-driven changes teams are implementing in their product processes.
📝 About This Content
This article is based on insights shared by Sachin Rekhi on LinkedIn.
📅 Originally posted on September 6, 2026 | View original post on LinkedIn →