# Capabilities

The primary object is not a project. The primary object is a capability.

## Proof Through Prototyping

Using functional, high-fidelity prototypes as strategic decision-making tools.

Principle: Prototypes are arguments.

Problems solved:
- Ambiguous product direction
- Slow decision cycles
- Teams debating abstractions without evidence

Evidence:
- Production-fidelity prototypes
- Code contributions
- Roadmap influence
- Reusable workflows

Tags: prototyping, strategy, design-engineering

## Visual Programming Systems

Designing tools that let domain experts create complex behaviors without writing code.

Principle: The right abstraction matters more than the surface UI.

Problems solved:
- Technical creation blocked by code-only workflows
- Complex behavior that is hard to inspect
- Domain experts depending on engineers for every change

Evidence:
- Visual authoring experiences
- Node-based workflows
- Complex system authoring made more inspectable

Tags: no-code, creator-tools, complex-ux, systems

## AI Behavior Design

Designing how AI systems suggest, act, explain, wait, and collaborate.

Principle: Design AI behavior, not just AI UI.

Problems solved:
- Unclear AI initiative
- Low trust in AI systems
- Chatbot-like interactions where agent behavior is needed

Evidence:
- Agent behavior principles
- AI interaction patterns
- Human-AI collaboration models

Tags: AI, agents, interaction-design, human-AI-collaboration

## Creator Economy Design

Designing systems where creators can publish, sell, and earn from digital goods.

Principle: Trust is part of the product.

Problems solved:
- Digital goods that are hard to evaluate before purchase
- Creator value that is difficult to explain
- Marketplace flows that need confidence on both sides

Evidence:
- Digital commerce experiences
- Product detail and purchase-confidence patterns
- Creator revenue workflows

Tags: creator-tools, commerce, marketplace-ux, trust

## Designer Workbench

Creating environments where designers can use production-like components, local workflows, and AI to build faster.

Principle: Designers need working materials, not only static canvases.

Problems solved:
- Design work disconnected from production components
- Slow prototype loops
- AI-assisted design work without reusable local workflows

Evidence:
- Local prototyping workflows
- AI-assisted design sandboxes
- Production-grade component experiments

Tags: design-engineering, AI, prototyping, workflows

## Organizational Enablement

Turning personal expertise into reusable systems, templates, workshops, documentation, and coaching.

Principle: Enablement beats gatekeeping.

Problems solved:
- Expertise trapped in one person
- Teams repeating the same setup work
- Designers needing practical ways to adopt new workflows

Evidence:
- Reusable systems and tools
- Workshops and coaching
- AI-powered workflow adoption

Tags: enablement, systems, design-systems, AI