AI Is Changing More Than Jobs. It’s Changing How We Organize Work. For decades, organizations have been structured around specialized job titles: software engineer, product manager, designer, operations manager, and analyst. Each role had defined responsibilities, clear boundaries, and a place on the organizational chart.
But according to Boris Cherny, creator of Anthropic’s Claude Code, those boundaries are beginning to disappear.
In a recent post that sparked widespread discussion across the technology industry, Cherny suggested that traditional functions such as engineering, product, and design are increasingly “melting into one.” Rather than organizing teams around narrow disciplines, he believes the future of work may be organized around a set of flexible archetypes that describe how people contribute to building products.
As Cherny asked:
“Maybe product roles of the future will look more like this, and less like the domain-specific roles of today?”
The Five AI-Era Work Archetypes
Based on his experience building Claude Code, Cherny identified five core archetypes that exist across his team:
- The Prototyper
The Prototyper creates new ideas, experiments rapidly, and explores possibilities. Most prototypes never ship, but the value lies in discovering new opportunities and testing assumptions quickly. - The Builder
The Builder transforms successful ideas into production-grade systems. Their focus is execution, reliability, architecture, and turning concepts into products that customers can actually use. - The Sweeper
The Sweeper optimizes, simplifies, refactors, and improves existing systems. They reduce complexity, increase performance, eliminate technical debt, and ensure products remain maintainable over time. - The Grower
The Grower focuses on iteration and expansion. Their role is to adapt products to market feedback, discover new use cases, and continuously improve customer value. - The Maintainer
The Maintainer ensures that products remain secure, reliable, efficient, and scalable as they mature. They provide the operational foundation that allows organizations to continue growing.
According to Cherny, most individuals naturally span multiple archetypes, and the balance between them changes depending on the maturity of the product and the needs of the organization.
Why Traditional Job Titles Are Breaking Down
The emergence of AI is accelerating a trend that has been building for years: the collapse of rigid functional boundaries.
Historically, organizations required specialized roles because knowledge and execution capabilities were scarce. Product managers managed requirements, engineers wrote code, designers created interfaces, and operations teams managed deployment.
AI changes that equation. A single individual equipped with modern AI tools can increasingly prototype, build, design, test, document, and deploy products independently. As a result, organizations may begin optimizing less for specialization and more for adaptability.
This helps explain why other technology leaders are making similar observations. Figma CEO Dylan Field recently suggested that everyone is becoming a “product builder,” while other organizations are replacing traditional management structures with roles such as “player-coaches” and “organizational leads.”
AI Doesn’t Replace These Roles. It Amplifies Them
One of the more interesting discussions emerging from Cherny’s framework concerns the relationship between these archetypes and AI itself.
When asked whether AI would eventually replace roles such as Builders and Sweepers, Cherny offered a broader perspective:
“Claude can help with all of these to varying extents, and will improve over time.”
This observation highlights an important reality of modern AI systems. AI is not simply automating one specific function. Instead, it is becoming a general-purpose capability layer that can augment nearly every type of knowledge work.
Prototypers can use AI to generate ideas faster. Builders can accelerate software development. Sweepers can identify technical debt and optimization opportunities. Growers can analyze markets and customer behavior. Maintainers can automate monitoring, security, and operational workflows.
The question may no longer be whether AI replaces a role, but how much of every role becomes AI-assisted.
Flexibility May Become the Most Valuable Skill
Not everyone agrees that archetypes should replace traditional job descriptions.
Kun Chen, a former executive at Microsoft and Meta, argued that assigning individuals to fixed archetypes risks creating new silos. Instead, he suggested that workers should remain adaptable and continually evolve their capabilities.
Cherny agreed:
“Totally agree. Roles often change over time/project.”
This may ultimately be the most important lesson from the discussion. The future of work may not belong to specialists who optimize a single skill for decades. It may belong to individuals who can move fluidly between creation, execution, optimization, growth, and operations.
The Real Organizational Shift
The broader implication of Cherny’s framework extends beyond software engineering.
As AI systems become capable of performing increasingly specialized tasks, organizations may stop structuring themselves around functions and begin structuring themselves around outcomes.
The traditional organizational chart was designed for a world where human labor was scarce and specialized expertise was difficult to acquire.
The AI-era organizational chart may look very different: smaller teams, broader responsibilities, fluid roles, and individuals who move between multiple archetypes depending on the problem being solved.
In that world, your future job title may matter less than your ability to adapt.
Sources: Boris Cherny (Anthropic Claude Code), Dylan Field (Figma), public discussions on AI-era organizational design and workforce transformation.
