PROMPT
ENGINEERING

I design structured, production-ready prompts that transform large language models into usable product experiences. Blending UX strategy, system thinking, and AI behavior design.

I design structured, production-ready prompts that transform large language models into usable product experiences. Blending UX strategy, system thinking, and AI behavior design.

Gen AI

Gen AI

Figma Make

Figma Make

UX/UI

UX/UI

Prototyping

Prototyping

Gen AI

Gen AI

CLIENT

Lanford Inc

PROJECT DURATION

Current

Overview

I design structured, testable, and production-ready prompts that transform large language models into usable, scalable product experiences. My work bridges UX strategy, system thinking, and AI behavior design.

APPROACH

Prompt engineering isn’t magic — it’s interaction design for probabilistic systems.
I approach AI the same way I approach product design:

Prompt engineering isn’t magic — it’s interaction design for probabilistic systems.
I approach AI the same way I approach product design:

Prompt engineering isn’t magic — it’s interaction design for probabilistic systems. I approach AI the same way I approach product design:

Intent Modeling

Intent Modeling

Define user goals, context, and edge cases so the model responds with clarity and relevance.

Behavioral Framing

Behavioral Framing

Responsive

Shape tone, role, and constraints to guide outputs while reducing risk and drift.

Output

Output

Design prompts that produce consistent, schema-aligned responses ready for production.

Iteration

Iteration

Future Proof

Refine through testing, versioning, and output evaluation to improve reliability and performance.

CASE STUDIES

These case studies showcase applied prompt engineering within real product contexts. Each example highlights the problem space, prompt architecture, constraints, and iteration strategy used to transform AI capabilities into structured, reliable experiences.

These case studies showcase applied prompt engineering within real product contexts. Each example highlights the problem space, prompt architecture, constraints, and iteration strategy used to transform AI capabilities into structured, reliable experiences.

These case studies showcase applied prompt engineering within real product contexts. Each example highlights the problem space, prompt architecture, constraints, and iteration strategy used to transform AI capabilities into structured, reliable experiences.

Smarter Rewards. Stronger Retention.

Smarter Rewards. Stronger Retention.

Smarter Rewards. Stronger Retention.

Smarter Rewards. Stronger Retention.

An end-to-end loyalty experience that connects rewards, challenges, and tier progression to measurable engagement behaviors—driving frequency, higher order value, and long-term brand affinity.

An end-to-end loyalty experience that connects rewards, challenges, and tier progression to measurable engagement behaviors—driving frequency, higher order value, and long-term brand affinity.

View Prototype
View Prototype

Next-Generation Contractor Experience

Next-Generation Contractor Experience

Next-Generation Contractor Experience

Next-Generation Contractor Experience

This prototype explores how predictive inventory insights and real-time order tracking can reduce downtime and decision friction for professional contractors. The experience bridges e-commerce infrastructure with jobsite intelligence.

This prototype explores how predictive inventory insights and real-time order tracking can reduce downtime and decision friction for professional contractors. The experience bridges e-commerce infrastructure with jobsite intelligence.

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View Prototype

Putting Users First in Open Enrollment

Putting Users First in Open Enrollment

Putting Users First in Open Enrollment

Putting Users First in Open Enrollment

Created a mobile-first, intuitive iOS app that helps users navigate complex health plan choices with ease. Contextual trays, progressive disclosure, and an AI assistant provide personalized guidance, minimizing cognitive load while keeping interactions fast and accessible.

Created a mobile-first, intuitive iOS app that helps users navigate complex health plan choices with ease. Contextual trays, progressive disclosure, and an AI assistant provide personalized guidance, minimizing cognitive load while keeping interactions fast and accessible.

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View Prototype

From Reactive Banking to Predictive Clarity

From Reactive Banking to Predictive Clarity

From Reactive Banking to Predictive Clarity

From Reactive Banking to Predictive Clarity

Traditional financial apps are built around static transaction feeds. But users don’t need more data—they need foresight. This solution addresses the gap between awareness and action by detecting micro-patterns in spending behavior, projecting future impact, and providing contextual interventions before problems compound.

Traditional financial apps are built around static transaction feeds. But users don’t need more data—they need foresight. This solution addresses the gap between awareness and action by detecting micro-patterns in spending behavior, projecting future impact, and providing contextual interventions before problems compound.

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View Prototype

Stabilizing Demand in a Volatile Supply Chain

Stabilizing Demand in a Volatile Supply Chain

Stabilizing Demand in a Volatile Supply Chain

Stabilizing Demand in a Volatile Supply Chain

Built for planners operating in high-variability environments, this experience combines real-time analytics, scenario modeling, and transparent AI explanations in a clean, modern interface. The result: lower cognitive load, higher forecast trust, and fewer costly overcorrections.

Built for planners operating in high-variability environments, this experience combines real-time analytics, scenario modeling, and transparent AI explanations in a clean, modern interface. The result: lower cognitive load, higher forecast trust, and fewer costly overcorrections.

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View Prototype

Probabilistic Insight for High-Risk Markets

Probabilistic Insight for High-Risk Markets

Probabilistic Insight for High-Risk Markets

Probabilistic Insight for High-Risk Markets

Built as an AI-powered anomaly detection engine, this prototype surfaces statistically significant volume spikes, breakout confirmations, and sentiment shifts — translating complex market behavior into structured opportunity scores and risk diagnostics. The result is a data-forward experience that reduces emotional decision-making in high-volatility environments.

Built as an AI-powered anomaly detection engine, this prototype surfaces statistically significant volume spikes, breakout confirmations, and sentiment shifts — translating complex market behavior into structured opportunity scores and risk diagnostics. The result is a data-forward experience that reduces emotional decision-making in high-volatility environments.

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View Prototype

The Ingredients: Designing the System Behind the Experience

The Ingredients: Designing the System Behind the Experience

The Ingredients: Designing the System Behind the Experience

The Ingredients: Designing the System Behind the Experience

“The Ingredients” is a comprehensive design system created to standardize components, streamline cross-platform development, and unlock faster innovation across Papa Johns digital products. Built with tokens, governance, and motion in mind, it aligns brand integrity with operational efficiency.

“The Ingredients” is a comprehensive design system created to standardize components, streamline cross-platform development, and unlock faster innovation across Papa Johns digital products. Built with tokens, governance, and motion in mind, it aligns brand integrity with operational efficiency.

View Prototype
View Prototype