We Kissed Specs and PRDs Goodbye. Product Managers Pass POCs Now.
Nobody looks forward to backlog grooming. Nobody ever did. AI made it possible to skip the ceremony and hand engineering a working proof of concept instead of a story card. Here is what changes when you let it.
Capability is the only durable AI moat. Tooling is rented; capability compounds.
Reorient product development around direct customer validation.
The shift from descriptive artifacts to executable proofs of concept reduces the cost and time of product validation. This allows for direct iteration with customers without consuming engineering resources.
Value translation layers, such as extensive documentation and estimation ceremonies, introduce overhead and delay, obscuring rather than clarifying intent. Their necessity diminishes as generative AI lowers the cost of prototyping.
Product managers capable of creating functional prototypes with AI agents enable faster feedback loops and ensure engineering effort is applied only to validated solutions.
The unit of work evolves from abstract story cards to concrete, validated proofs of concept, changing capacity planning from an estimation exercise to a strategic investment decision.
Organizations must invest in product capability development, enabling direct validation and iteration with customers, to fully leverage AI's potential in the product development lifecycle.
Capability is the only durable AI moat. Tooling is rented; capability compounds.
Reorient product development around direct customer validation.
The shift from descriptive artifacts to executable proofs of concept reduces the cost and time of product validation. This allows for direct iteration with customers without consuming engineering resources.
Value translation layers, such as extensive documentation and estimation ceremonies, introduce overhead and delay, obscuring rather than clarifying intent. Their necessity diminishes as generative AI lowers the cost of prototyping.
Product managers capable of creating functional prototypes with AI agents enable faster feedback loops and ensure engineering effort is applied only to validated solutions.
The unit of work evolves from abstract story cards to concrete, validated proofs of concept, changing capacity planning from an estimation exercise to a strategic investment decision.
Organizations must invest in product capability development, enabling direct validation and iteration with customers, to fully leverage AI's potential in the product development lifecycle.
After 20 years in software development, Norman is both a hands-on leader and defining the new age of AI SDLC for some of the biggest brands in the world — and exploring it with the builders. He writes here about things he is hearing and seeing. All posts are his personal points of view and do not reflect any employer or any customer he has ever had contact with.
The views and opinions expressed in this article are the author’s own and do not represent the positions of any employer, client, or affiliated organization.
