Boris Cherny Looks Ahead to New Prototypes of Product Roles in the AI Era
Boris Cherny believes that as roles in engineering, product, design, and data science merge into new forms, the Claude Code team presents five prototypes: Prototyper (generating numerous new ideas), Builder (turning prototypes into production-ready), Sweeper (optimizing UI and code), Grower (iteratively improving PMF), and Maintainer (ensuring scalability of mature systems).
Healthy teams need to mix these prototypes according to the product stage, rather than relying on traditional domain-specific roles.
In terms of market mechanisms, the integration of AI roles accelerates the flattening of corporate organizational structures, with funding shifting towards flexible multi-role talents and AI collaboration tools. Event-driven recruitment and team-building transformations benefit those who adapt to multi-prototype talents and productivity platforms, while traditional vertical functional division models face pressure.
Source: Public Information
ABAB AI Insight
Boris Cherny observes that in cutting-edge AI teams like Anthropic, designers, engineers, and PMs have crossed traditional boundaries, reflecting the higher demands for comprehensive delivery capabilities as AI lowers the barriers for single skills.
The capital path indicates that tech companies are shifting their human resource budgets from vertical recruitment to multi-skilled composite talents and collaborative tools, motivated by the need to accelerate the iteration cycle from prototype to scale, strategically building efficient team structures suited for the AI era.
Similar to the evolution from pure engineers to full-stack developers in the internet era, the current AI era is at a critical stage of transforming product roles from domain specialization to multi-prototype integration.
This fundamentally belongs to technological substitution, with the mechanism being that AI significantly compresses repetitive tasks like coding and design, forcing value creation to concentrate on idea generation, optimization iteration, and scale maintenance. Capital and talent are concentrating on individuals and teams with multi-role capabilities, and pricing power is shifting from traditional functional divisions to comprehensive contributors who can cover the entire product lifecycle.
ABAB News · Law of Cognition
Single skills are temporarily scarce, while multi-role delivery is everlasting; AI liberates expertise but tests comprehensiveness.
Prototype iteration is temporary, while scale maintenance is everlasting; product stages determine role ratios.
Engineers write code temporarily, while deliverers cross prototypes for a lifetime; top talents sell full-cycle product structural capabilities.