At CYFRON SOFTWARE TRADING, we believe thoughtful design and clean development practices are foundational to building interfaces that not only look good but also work well at scale. A recent development exercise—a live walkthrough of building a simple chat app powered by GPT-4—offered valuable insight into how UI/UX design, AI-powered coding, and functional interactivity intersect within modern web apps.
Rather than leaning on aesthetics first and fixing logic later, the process started in Figma with design fundamentals: auto-layouts, consistent variables, organized layer naming, and responsive containers. These aren’t just visual tactics—they directly impacted how easily the design could be transformed into code, particularly when integrating tools like Figma’s Multi-Code Processing (MCP) server. These best practices are what make a design both expressive and machine-readable.
On the development side, the app was built using Next.js with TypeScript and Tailwind CSS. With Cursor (an AI-powered code editor) in the mix, components were translated from Figma directly into HTML and CSS—with variable retention and consistent spacing preserved. AI tools were used not to replace the developer, but to accelerate initial scaffolding. This collaborative mode between designer, developer, and machine is something we see increasingly often, and it's central to future-ready workflows.
One of the most useful implementations came with the OpenAI integration. Responses from the language model were streamed character-by-character, creating a realistic typing effect—an example of how fine-grained interaction details can significantly elevate UX. Commands like "change the background color" were parsed by the AI and used to trigger frontend updates, bridging natural language with interface logic.
Animations such as expandable chat boxes, scrollable areas, and context-aware color changes were not just embellishments—they were thoughtfully layered on top of a well-structured layout. This highlights a key philosophy we value: micro-interactions should be driven by usability, not trend.
Version control tied the entire workflow together with Git/GitHub. A custom cursor.md file acted as ongoing documentation for AI assistants—capturing the evolution of the project to support better context in future coding prompts.
Even when using powerful models like GPT-4 or GPT-5, results were only as clear as the structure they were built upon. Bugs and constraints were handled not with brute force prompting but with debugging rooted in logic. “AI coding” here is not a shortcut—it’s a companion to structured problem-solving.
The final output was a responsive, functional AI chat interface—an example of what’s possible when manual precision and AI tooling work in harmony. For product teams, this approach reinforces the value of good interface planning and modular design systems. For developers, it shows how AI tools can meaningfully augment the creative process without sacrificing cleanliness or control.
At CYFRON, we approach every solution with a commitment to usability, innovation, and clarity. This project illustrates how the next generation of app development can stay grounded in those values—even as AI becomes more embedded in every click, action, and pixel.