Transforming UX Design with GPT

Table of Contents

1. Introduction
2. The Goal of Working with GPT
3. The Disappointment with GPT4
4. Use Case: Scheduling Workshops
5. The UI Design Process
   1. Landing Page Design
   2. Workshop Selection
   3. Calendar View
   4. Time Slot Selection
6. GPT's Assistance with UI Design
7. Reviewing the Generated Code
8. Challenges and Improvements
9. Taking Control of the Code
10. Final Thoughts

Article

Working with GPT: Designing a Workshop Scheduling System

Introduction

In this article, we will explore the process of designing a workshop scheduling system using GPT (Generative Pre-trained Transformer). GPT is a large language model developed by OpenAI that has demonstrated remarkable capabilities in generating human-like text. We will discuss its potential to assist in UI design and specifically focus on a use case for scheduling workshops. However, our Journey with GPT is filled with both excitement and disappointment as we unravel the complexities of working with this advanced technology.

The Goal of Working with GPT

Our initial goal was to leverage GPT4's impressive capabilities to generate code for a web page Based on UI mock-ups or wireframes. We had hoped to feed it images and have it automatically generate code for us. Unfortunately, we quickly discovered that this feature was not available to the public. Instead, GPT4 suggested describing the UI to it. Although disappointed, we decided to embrace the challenge and describe the UI for our workshop scheduling system.

Use Case: Scheduling Workshops

The workshop scheduling system we aimed to design would allow designated client representatives to log in and schedule workshops for their companies. One particular use case involved Angela Reed from Acme scheduling a half-day training workshop. The UI for this use case would include a landing page, workshop selection options, a calendar view, and a time slot selection feature. While the details of this use case are not crucial for our discussion, we will illustrate the process using a storyboard.

The UI Design Process

1. Landing Page Design: The designated representative would have a landing page or console where they can view their scheduled workshops. Initially, Angela Reed has no workshops scheduled, but she can click on the "Schedule Workshop" button to proceed.

2. Workshop Selection: Clicking the "Schedule Workshop" button takes Angela to a more complex page. Here, she can select the desired workshop and the preferred demonstration language for her company. The bottom section includes a month calendar view and time slot view for selecting the date and start time of the workshop.

3. Calendar View: It is essential to display available and unavailable dates clearly in the calendar view. Grayed-out dates indicate unavailability, while clickable dates are available for workshop scheduling. Selected dates are highlighted in a light yellow or orange color.

4. Time Slot Selection: For each selected date, Angela can choose the start time for her workshop. Similar to the calendar view, available time slots have clickable links, while unavailable time slots do not. The selected start time is highlighted accordingly.

GPT's Assistance with UI Design

We approached GPT to help us with the challenging task of generating the calendar view and time slot selection feature. We had to provide a precise description of the web page's UI elements and their behaviors. After investing considerable time and effort into refining the specification, we requested GPT4 to provide the HTML code for the desired UI layout. The generated code showed promise and aligned with our design expectations.

Reviewing the Generated Code

We received the generated HTML code and incorporated it into our web project. The code reflected the bootstrap framework and adhered to the desired UI layout. However, there were some issues, such as missing elements for the user Avatar and workshop/demonstration language selection. We had to request further assistance from GPT and ensure the code provided these missing elements.

Challenges and Improvements

As we delved deeper into refining the code, we encountered challenges and improvements that needed to be addressed. The generated code contained both Core logic and display logic, making it less maintainable. We decided to reorganize the code by separating responsibilities into a model, view, and controller. Although these changes brought some Clarity, there were still areas where the logic remained unclear. We had to repeatedly ask GPT for explanations and clarity on specific methods and functionalities.

Taking Control of the Code

Despite GPT's assistance in generating code, we realized that we needed to take control. The code generated by GPT often lacked vital elements or didn't adhere to our requirements. It became apparent that manually coding the UI ourselves and seeking assistance from GPT for specific challenges was a more effective approach. We learned the importance of integrating GPT's suggestions into our code promptly and testing the functionality rigorously.

Final Thoughts

Working with GPT proved both exciting and challenging. While it showcased its ability to assist in UI design, especially in simpler scenarios or providing programming guidance, it struggled to meet the complex requirements of a real-world application. GPT's generated code often required further refinement and extensive modifications to match our desired outcomes. However, it served as a valuable tool to validate our own code and gain insights into alternate approaches. In the next video, we will explore GPT's capabilities in handling more complex business rules and discuss its potential role in the future of software development.

Highlights

• GPT's capabilities in UI generation and code assistance are both impressive and disappointing.
• Designing a workshop scheduling system using GPT as a guiding tool.
• The UI design process includes landing page, workshop selection, calendar view, and time slot selection.
• GPT's assistance in generating HTML code for the desired UI layout.
• Reviewing, refining, and integrating GPT's code into our web project.
• Challenges and improvements in separating core logic and display logic.
• Taking control of the code and combining GPT's suggestions with manual coding.
• GPT's limitations in meeting complex real-world application requirements.
• The utility of GPT as a validation tool and gaining insights into alternate approaches.
• Exploring GPT's capabilities in handling complex business rules in software development.

FAQ

Q: Can GPT4 generate code directly from UI mock-ups or wireframes? A: No, this capability is not available to the general public. GPT4 can only generate code based on textual descriptions of the UI.

Q: How accurate is GPT's generated code in terms of adhering to design expectations? A: GPT's generated code provides a starting point, but it often requires further refinement and modifications to align with design requirements.

Q: How did GPT Assist in the UI design process? A: GPT helped by providing HTML code for the desired UI layout, including the calendar view and time slot selection feature.

Q: Did GPT's generated code meet all the requirements of the workshop scheduling system? A: No, the generated code lacked certain elements and required manual adjustments to match the desired outcomes.

Q: Can GPT4 handle more complex business rules beyond UI design? A: While GPT4 has its limitations, it can still provide guidance in handling complex business rules, as explored in the upcoming video.