Job seekers were struggling to keep track of multiple applications, interviews, and status updates in a simple, centralized way. The challenge was to create a solution that would streamline this process while being intuitive and mobile-friendly. To bring this solution to life, I taught myself Android Studio, taking full ownership of both the design and development phases.

Through user interviews and market research, I identified the key frustrations job seekers faced: the need for visual tracking, quick updates, and accessible application information on the go. This research shaped the app’s core functionalities and UX. Leveraging AI Language Learning Models (LLMs), I also enhanced my ability to quickly code and prototype features in Android Studio.

Starting with sketches and wireframes, I focused on creating a clean, intuitive layout that would allow users to quickly add new jobs, track their application status, and easily update information. The design centered around visual clarity and minimizing user effort. AI-assisted coding played a key role in converting wireframes into a functional prototype swiftly.

After building an interactive prototype, I conducted user testing to validate the design. Feedback led to improvements in the navigation, such as adding a search function and refining the color coding system for job statuses to enhance usability. I used AI LLMs to assist in refining the code based on user feedback, ensuring quick iterations and more efficient development.

Learning Android Studio from scratch, I designed and developed the app entirely on my own. Using AI to assist in coding tasks, I ensured the UI was fully responsive across mobile devices, focusing on maintaining the visual hierarchy and easy touch interactions for job updates and status changes.

The final app allows job seekers to track applications with ease, providing a visual overview of their job search. The app is currently in the closed testing phase, but initial feedback has been very positive, with users praising its simplicity and functionality. Early testing shows that 85% of users feel more organized in their job search after using the app.

Looking ahead, I plan to introduce a resume upload feature and integration with LinkedIn to further streamline the job search process. As the app moves towards public release, AI will continue to assist in the development of these features, helping to iterate and implement them quickly.

As both a designer and a home project enthusiast, I was always looking for a list app that fit my workflow. However, none of the existing solutions had the specific features I needed to organize my projects effectively. So, I decided to create my own! The goal was to help break down large projects into simple, easily achievable tasks, creating a flow that leads to project completion—a 'Task Flow' if you will.

While plenty of task and list apps exist, TaskFlow stands out due to its unique organization, user interface, and incentive features that drive productivity.

I wanted the app to feel simple but powerful, with large, prominent titles and buttons for ease of use. At the same time, it needed enough depth and features to make it functional for a variety of projects. The main focus was on a UI that allows each project to stand out visually, showing key information—like the number of tasks left—at a glance.

• Color-Coded Progress: Projects are automatically color-coded based on progress: Red for no completed tasks, gradually transitioning to Green for fully completed projects. This visual indicator creates a sense of urgency for tasks that need more attention.
• Icons for Categories: Projects are organized into categories like Home, Yard, and Work, each represented by intuitive icons for quick visual recognition of tasks.
• Flow is Key: The app’s task flow is its central feature. I focused on making it simple and intuitive for users to see their tasks, including whether those tasks have sub-tasks, and to navigate projects efficiently without any friction.

My design process typically starts with sketches, Figma, or Figjam, but for TaskFlow, I jumped straight into Figma to begin creating screens. I believe interacting with a design as you create it helps you better understand the user experience, and Figma’s prototyping features allowed me to test and iterate on the flow as I designed it.

• Interactive Prototyping: Creating a working prototype was essential. Every click, swipe, and scroll was tested from the user’s perspective to ensure a smooth experience.
• AI-Assisted Development: While I’m still in the design phase, I plan to use AI LLMs to assist in development, as I did in my previous projects. Leading AI in this process is both faster and more challenging, as you have to guide it with precision, compared to leading a team of designers or developers. It’s crucial to define tasks clearly to get the desired output efficiently.

Although TaskFlow is still in the design phase, the app’s early Figma prototypes have demonstrated a user-friendly experience and a unique flow that breaks projects into manageable tasks. This project showcases my design skills, research abilities, and leadership in guiding AI-driven development processes. By identifying gaps in existing apps, I've been able to create something new that caters to users like me who want a simple yet powerful way to manage projects.

INSP, a western-themed television station, wanted to promote their network through an online store selling branded merchandise like t-shirts, hats, and even bath rugs. As the Senior UX/UI Designer, I was tasked with creating the mockups for this shop. What began as a simple e-commerce task quickly evolved into something more significant—an innovative solution for selling to INSP’s primary demographic of 60+ viewers.

The challenge? Creating a 'no-shop shop.' The network didn’t want to handle packaging or shipping, and all transactions were routed to external sites. My task was to design an online store that was intuitive for older users, who could browse products seamlessly and complete transactions on multiple third-party sites without confusion or hesitation.

The first step was to find reliable print-on-demand and drop-shipping companies that could fulfill orders. But the real design challenge was ensuring that users—many over 65—would trust and feel comfortable navigating a site that took them to unfamiliar external sites for purchases.

• Designing for Trust: I needed to ensure the transition from browsing to purchasing on external sites felt secure and familiar to users. The design had to foster trust, using simple navigation, clear call-to-actions, and reassuring messaging.
• Tailored Visuals for the Audience: One of the key insights was the importance of using visuals that resonated with INSP’s demographic. This meant showcasing models closer in age to our target audience, which presented a problem—traditional stock photos didn’t cater to this age group.

During the prototype phase, I began experimenting with early generative AI models to fill in the gaps for imagery. While the initial results were basic, it allowed me to demonstrate to stakeholders the potential of using models in our key demo to better represent the brand.

As AI models rapidly improved, I proposed AI-generated imagery as a cost-effective alternative to photoshoots. This allowed us to create custom visuals without the need for expensive production, saving thousands of dollars in marketing and design costs. This shift led to increased profitability for the store and sparked broader AI adoption across the company.

My design process started with creating mockups and prototypes in Figma. I presented these to stakeholders, including company VPs and EVPs, and incorporated their feedback. Working closely with the product manager, I collaborated with both front- and back-end developers to bring the designs to life in an Agile environment, complete with bi-weekly Sprints and weekly SCRUM sessions.

I also led User Acceptance Testing (UAT), ensuring that the final product met the needs of our users and stakeholders alike. The entire project emphasized ease of use for older audiences, a consistent user flow, and trust-building throughout the shopping experience.

The result was an innovative online store that created a new revenue stream for INSP while increasing site engagement by 12%. By wearing branded apparel, viewers became walking advertisements for the network, creating a new layer of brand visibility.

My biggest achievement, however, was integrating generative AI into this project and showing upper management the potential for AI in other areas of the business. This led to the adoption of AI across marketing, design, production, and development teams, transforming the company's workflow and reducing costs.

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