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01

Capabilities

Diagnose, direct, make, and guide delivery.

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02

EEM

A complete operating model for executable experience work.

Enter the EEM system
03

Work

Complete stories from complex product and service environments.

Explore workRecreation.gov
04

Thinking

Ideas about experience, organizations, AI, and decision-making.

Explore all thinking
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Back to EEM Overview

06 Team structure

Team Structure & Roles

Directors, stewards, and partners built for executable work.

How Teams Change in the EEM Era

AI-enabled workflows don't just change tools—they change how teams are structured, how roles are defined, and how people collaborate.

Traditional Teams
  • Clear handoffs between specialized roles
  • Sequential stages (research design build)
  • Figma as source of truth
  • Engineering implements from specs
EEM Teams
  • Collaboration throughout Execute stage
  • Shared ownership of governance
  • Code (Storybook) as source of truth
  • Cross-functional fluency expected

Traditional vs. EEM Team Comparison

Aspect Traditional EEM
Workflow Sequential handoffs Collaborative throughout
Source of Truth Figma files Code (Storybook, component library)
Designer Output Static mockups Functional prototypes
Learning Mode Plan, then build Build to learn
Iteration Speed Sprints Hours
Skill Overlap Specialized silos Cross-functional fluency
Governance Implicit (done = ship) Explicit (deliberate decision)

The Four EEM Roles

EEM teams organize around four key roles. These aren't job titles—they're functional responsibilities that might be held by one person or distributed across a team.

01

Execution Designer

The Evolved Designer Role

Hybrid maker-evaluators who direct Agent IDEs to build functional prototypes. They don't write code—they direct AI agents, evaluate outputs, and iterate rapidly on multiple solution variants.

What They Do

  • Direct AI agents to build functional prototypes
  • Evaluate brand/UX quality in code
  • Iterate rapidly on multiple solution variants
  • Present solutions at governance

Skills Required

  • Prompt literacy & Agent IDE fluency
  • Design judgment in working software
  • Component thinking (props, states, variants)
  • Design system fluency

Critical: Execution Designers don't need to be expert coders. They need comfort with code and the ability to evaluate working software. The Agent IDE does the coding—the designer does the directing and evaluating.

Background
Design + basic code comfort OR Code + strong design sense
Look for
Portfolio showing rapid iteration, comfort with technical constraints, evidence of learning orientation
Red flags
Pixel-perfect perfectionism, resistance to code, “handoff mentality,” discomfort with ambiguity
02

Design System Steward

System Governance & Evolution

Governs the design system, evolves patterns based on validated solutions, maintains brand consistency, and educates the team on system usage. The design system is a critical input constraint in EEM.

What They Do

  • Govern design system components & tokens
  • Evolve patterns based on validated solutions
  • Maintain brand consistency
  • Approve new pattern additions

Skills Required

  • Deep component/token knowledge
  • Brand/consistency judgment
  • Documentation skills
  • System architecture thinking
Background
Design systems experience, strong documentation skills, governance experience
Look for
Educator mindset, strategic thinking, evidence of evolving systems over time
Red flags
Rigid rule enforcement, lack of evolution mindset, “design police” attitude
03

Product Strategist

Input Definition & Solution Judgment

Defines inputs (research, goals, hunches), judges solutions at governance gate, prioritizes what ships, and connects business strategy to execution. They operate at the boundaries of the EEM flow.

What They Do

  • Define inputs (research, strategic direction, hunches)
  • Judge solutions at governance gate
  • Prioritize what ships
  • Connect business strategy to execution

Skills Required

  • Research synthesis & strategic framing
  • Solution evaluation (can judge working software)
  • Prioritization judgment
  • Cross-functional facilitation
Background
Product management + design thinking, experience with research synthesis
Look for
Judgment under uncertainty, synthesis skills, stakeholder management
Red flags
Need for complete information before deciding, micro-management, resistance to hunches
04

Production Engineer

Production Implementation & Quality

Architects scalable implementations from validated experiments. Refines solutions for production readiness, optimizes performance, maintains technical quality, and partners in governance handoff.

What They Do

  • Architect scalable implementations
  • Refine solutions for production readiness
  • Optimize performance
  • Partner in governance handoff (accept/reject readiness)

Skills Required

  • Design judgment (enough to evaluate UX)
  • System architecture
  • Performance optimization
  • Collaborative approach
Background
Frontend engineering + design appreciation, system thinking
Look for
Quality mindset, collaborative approach, interest in UX, attention to detail
Red flags
“Just tell me what to build” attitude, resistance to design input, speed-over-quality mindset

Transition Paths for Existing Teams

How do existing roles evolve into EEM roles? Here are common transition paths.

  1. Product Designer

    Execution Designer

  2. Design Systems Lead

    Design System Steward

  3. Product Manager

    Product Strategist

  4. Frontend Engineer

    Production Engineer

  5. UI Developer / Design Technologist

    Execution Designer

Transition Guidance

  • Start with mindset, not skills. The biggest shift is from “I create artifacts” to “I create outcomes through AI collaboration.”
  • Learn by doing. The best way to develop EEM skills is to start using Agent IDEs on real projects, even small ones.
  • Value cross-functional experience. People who've worked across disciplines adapt faster to EEM roles.

What Makes EEM Teams World-Class

Speed

  • Weeks of planning collapse to days of making
  • Iteration cycles measured in hours, not sprints
  • Governance decisions made quickly with real evidence

Quality

  • Stakeholders see real things, not promises
  • Design system ensures consistency
  • Validated solutions reduce production risk

System

  • Design system evolves based on real usage
  • Feedback loops are tight
  • Knowledge compounds over time

Talent

  • Attracts people who want to make, not administrate
  • Values learning over credentials
  • Comfortable with ambiguity

Ready to Build Your EEM Team?

Whether you're hiring new talent or transitioning existing team members, let's discuss how to structure your team for AI-enabled workflows.

Let's Talk Back to EEM Overview

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