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AI Systems

Designing how AI interactions, outputs, and user experiences behave across generation, evaluation, and decision-making.

Focus areas: AI UX Writing, Content Design, AI Interaction Design, Prompt Systems, User Flows, Content Systems, Output Evaluation

AI Interaction Systems




VOICE DESIGN AI PROTOTYPE



 

System Logic

AI voice creation requires more than generation—it requires trust, consent, customization, and user control.

 



Method

* Design onboarding flow * Establish consent requirements
* Guide voice upload and analysis
* Structure customization options
* Support editing and export workflows




System Capabilities

* Guides AI interactions * Supports user trust
* Enables voice customization * Improves workflow clarity
* Creates consistent user experiences



What This Reveals

AI products succeed when users understand what the system is doing and maintain control throughout the process.

Also Demonstrates

UX Writing · Content Design · AI Interaction Design · User Flows · Information Architecture · Figma





MULTI-TURN INTERACTION SYSTEM





System Logic

AI interactions aren’t single responses—they’re sequences.
Clarity emerges as intent is refined across turns.




  Simplified Flow

Input → Intent → Response → Next

   Full System Flow

Input → Intent → Clarification → Response → Next Step → Fallback

     Before / After 

   Before (Unstructured Response)

* Generic output * No guidance * Dead end

  After (Structured Interaction)

* Clarifies intent * Guides next step * Adaptive flow


From reactive responses → guided, adaptive interactions



Method

* Map interaction flows * Define intent + edge cases * Structure for clarification + recovery
* Evaluate across turns



System Capabilities

* Maintains state * Disambiguates intent * Adapts to context * Guides toward resolution



What This Reveals

AI performs best when interactions are structured as sequences.

Also Demonstrates

AI tutoring · UX writing · structured communication






CONVERSATIONAL TONE SYSTEM





System Logic

Tone can be defined, tested, and controlled.



















Method

* Define tone variables * Generate variations * Compare clarity + perception
* Refine for context



System Capabilities

* Controls voice * Adapts tone * Maintains consistency



What This Reveals

Tone is a system—not a stylistic choice.

Also Demonstrates

Copywriting · Brand voice · adaptive language

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Generation Systems
 

AI CREATIVE WORKFLOW SYSTEM


 

 
System Logic

AI improves through iteration—not one-off prompts.





















Method

* Define intent * Generate outputs * Evaluate * Refine * Select



System Capabilities

* Structures generation * Reduces iteration cost * Improves consistency



What This Reveals

Direction—not generation—determines output quality.

Also Demonstrates

Art direction · prompt design · iterative thinking






 

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VARIATION & CONSTRAINT SYSTEM
 


 
System Logic

Constraints define outputs.



















Method

* Fix variables * Introduce variation * Generate outputs
* Compare + measure * Refine constraints



System Capabilities

* Controls variability * Enables comparison * Improves consistency



What This Reveals

Consistency comes from control, not randomness.

Also Demonstrates

Copywriting · art direction · testing systems





GENERATIVE CONSISTENCY SYSTEM


  

System Logic

Outputs depend on input structure.

 

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Consistent Outputs

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Prompt Variation

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Edge Conditions

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Failure Systems


MODEL FAILURE SYSTEM



 

System Logic

Failures are driven by ambiguity.

 

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Method

* Introduce ambiguous inputs * Generate outputs * Identify breakdowns * Analyze patterns



System Capabilities

* Identifies failure modes * Surfaces ambiguity
* Improves robustness



What This Reveals
Most failures come from unclear input—not weak models.

Also Demonstrates
AI tutoring · UX thinking · clarity design



SEGMENTATION FAILURE SYSTEM





System Logic

Perception breaks under complexity.


 

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Method

* Introduce visual noise * Generate outputs * Compare failures
* Analyze conditions



System Capabilities

* Identifies breakdowns * Evaluates robustness
* Surfaces edge cases



What This Reveals

AI perception fails when context becomes complex.

Also Demonstrates

Visual analysis · AI evaluation · edge case thinking



Object Segmentation System - NEW paste HERE

A system exploring how tone functions as a controllable variable within AI-generated responses



System Logic

Tone is not subjective—it can be structured, tested, and applied systematically.
By holding informational content constant and varying tone, this system examines how shifts in language alter perception, emotional response, and user experience.



Process

    •    Consistent input across tone variations
    •    Structured shifts in tone (neutral, supportive, creative)
    •    Evaluation of clarity, perception, and interaction




Outcome

A scalable system for generating consistent, human-centered responses across different tones and conversational contexts



System Capabilities

    •    Adapts tone based on user intent
    •    Maintains clarity across variations
    •    Produces consistent, usable responses
    •    Scales across conversational use cases


Perception Systems



OBJECT SEGMENTATION SYSTEM

 

System Logic

Perception is context-dependent.

 

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Method

* Provide inputs * Generate outputs * Compare accuracy
* Evaluate context



System Capabilities

* Detects boundaries * Evaluates context * Improves interpretation



What this reveals

Objects are understood through context—not isolation.

Also Demonstrates

Art direction · perception · evaluation




Exploration



COLOR IMPACT SYSTEM

 

System Logic

Small visual shifts change perception.

 

System Output

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Method

* Keep composition * Vary color * Compare outputs
* Evaluate perception



System Capabilities

* Controls tone * Shapes perception * Enhances clarity



What This Reveals

Perception is highly sensitive to visual input.

Also Demonstrates

Art direction · brand · visual storytelling



IDENTITY FRAGMENTATION SYSTEM

 

System Logic

Consistency requires constraints.

 

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Method

* Generate variations * Compare identity * Identify drift
* Analyze breakdown



System Capabilities

* Tracks consistency * Identifies drift * Improves control



What This Reveals


Without constraints, identity breaks down.

Also Demonstrates


Art direction · brand systems · narrative

© 2026 by Sarah A. Schmidt 

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