AI is a tool, not a replacement, but it must be used where it’s good—where it bridges the gaps between design and functionality.
The use of tools like Cursor and Windsurf in our workflows as UX-professionals eliminates the inefficiency of translating design into code, bringing design directly into the world of code. It makes design functional, actionable, and directly tied to implementation.
When we can use tools that unifies design and code, removing unnecessary layers and enabling designs to directly generate functionality delivered as prototypes or as packages ready for development. While Figma remains a powerful tool for collaboration, its AI enhancements are superficial – like the “paint on a car” – whereas AI driven IDE-tools provides the “engine and chassis.” That transforms design into a functional, integrated part of development, where code becomes the foundation for design execution.
Rethinking UX
The way we do web and app design today is iterative, slower than it needs to be. Tools like Figma dominate workflows, requiring manual creation of every detail before functionality can exist. Developers then interpret these designs into code, introducing delays, miscommunication, and inefficiency.
AI drive IDE-tools shows a path forward and used correctly it might change the way we work. By bridging the areas of design and code, it eliminates unnecessary steps, bringing design directly into the coding process and making design and functionality inseparable.
Figma vs. AI IDE: The paint vs. the engine
Figma is great for collaboration, prototyping, and visual design. But even as it integrates AI, it remains as a layer on top of the development process—designs still require developers to interpret and translate them into code.
Cursor and Windsurf, on the other hand, brings design into code, bridging the gap between what designers create and what developers build. By making designs functional from the start, these tools eliminates inefficiencies and ensures a seamless process.
This isn’t just about saving time – it’s about eliminating the disconnect between design and implementation. Every time a design is interpreted into code, something is lost. Tools that create code with the help of AI can bypasses this entirely, integrating design directly into the coding process.
The backbone of design
When we create designs in any software, every line, shape, or visual element is essentially code. These visual components are representations of underlying instructions – static functionality combined to form something new. Design software acts as a layer of abstraction, hiding the development beneath, but at its core, every design element is generated and defined by code.
When AI features are added to design tools, the same principle applies. The AI uses algorithms (code) to create visual outputs (also code). The key difference is that AI interprets inputs – your words, intentions, or data—to generate designs. However, this interpretation is never perfect. Automatic design tools often require manual adjustments, redrawing, and refinements because the AI’s understanding of creative intent is limited by its algorithms and training data.
The layers
The real power of blending design and code lies in exposing both layers – the underlying logic and the visual representation. By having access to the code behind the design, we can modify functionality and therefor be more precise in our intent: this also lets us understand what is shaping or breaking the visual output and functions. This duality enables us to tweak and perfect designs more effectively, merging creativity with precision.
Creativity meets problem solving
Design is ultimately about solving problems, whether they are small or large. While it can be easier to modify code, it’s harder to infuse it with creativity. AI can assist by providing starting points, interpreting inputs, and generating functional designs, but human input remains essential. The manual effort of refining, reshaping, and adapting the output ensures that the design aligns with its purpose.
This convergence of design and code represents a shift in how we approach problem-solving. Instead of seeing them as separate disciplines, they become two sides of the same coin—tools we use together to create, iterate, and refine solutions. AI accelerates this process, but the core idea remains that design is fundamentally code, and our ability to interact with both layers determines how well we solve the problems we face.
Rapid Prototyping and User Testing: Understanding Intent and Identifying Pitfalls
Rapid prototyping and user testing are critical steps to ensure that the intent of a design is not only understood but validated before implementation. By leveraging tools that unify design and code, we can quickly generate functional prototypes, enabling iterative testing in real-world conditions. This process exposes pitfalls early, allowing for adjustments and improvements before significant development time is invested.
Traditional workflows often prioritize visual representation, leaving functionality and usability testing to be performed with “static prototypes”. This delay increases the risk of discovering design flaws too late, leading to costly revisions. By adopting AI-driven tools like Cursor and Windsurf, we bridge the gap between ideation and functionality, creating prototypes that are not static representations but actual, testable solutions.
Key Benefits:
- Intent validation: Functional prototypes allow designers and stakeholders to test whether the design solves the intended problem early in the process
- Early pitfall detection: By observing real user interactions quick, we identify usability issues, misalignments, and unforeseen challenges early
- Iterative refinement: Designs can be adjusted quickly based on concrete feedback, rather than assumptions, ensuring alignment with user needs and business goals
- Efficiency: Rapid prototyping eliminates unnecessary layers and minimizes delays, as the design is already functional and ready for testing
Moving Beyond the Visual
Rapid prototyping transforms design from static visuals into actionable solutions, merging creativity with functionality. By understanding the underlying code layer and testing prototypes, we ensure that designs are not only visually appealing but also practical, user-centered, and aligned with real-world usage.
This approach reduces the disconnect between intent and execution, making design a truly integrated part of the development process—where testing validates solutions before they become problems.
Here’s the breakdown
- Code is the backbone of digital design. If a design can’t be coded, it doesn’t exist.
- Design should be functional. Instead of creating static designs, focus on making them actionable and integrated into the development process.
- AI is the enabler. Tools like Cursor bridges the gap, eliminating inefficiency and creating a unified workflow.
- This is not a solution for everything, but it is a path not taken. Figma is the solution to many of our tasks, but adapting our workflows with a broader adoption might be beneficial.
Final thoughts
The future of UX isn’t about abandoning creativity; it’s about removing inefficiencies. These tools shows how design can be seamlessly integrated into the development process, making workflows smarter and more aligned.
AI isn’t here to replace designers; it’s here to enhance our work. Cursor and Windsurf is a part of this transformation, bringing design into code and redefining how we create digital experiences.
Cursor is an AI-powered code editor designed to enhance developer productivity by integrating advanced AI features directly into the coding workflow. As a fork of Visual Studio Code, it supports existing extensions and settings, providing a familiar environment for users.
The Windsurf Editor by Codeium is an AI-integrated development environment designed to enhance developer productivity through seamless collaboration between human and AI. It introduces "AI flows," combining the collaborative aspects of copilots with the autonomous capabilities of agents, enabling the AI to assist in both simple and complex tasks.
Key features include code generation, smart rewrites, and codebase queries, enabling efficient code manipulation and navigation. The AI capabilities allow for predictive text completion, multi-line edits, and intelligent code suggestions, streamlining the development process. Additionally, it offers a chat query function for codebase inquiries, facilitating seamless communication and collaboration within the development environment.