Product Managers Can Now Prototype in Code, So What's the Role of Design?
Do companies still need designers now that product managers can prototype directly in code? The answer is yes, but not in the way most teams are used to. For years, the typical product development workflow followed a familiar pattern, and the handoff from design to development has always been problematic.
Designers create beautiful mockups in Figma, and developers interpret those mockups and rebuild them in code. In theory, this process created a smooth handoff between the design and development teams. However, in practice, somewhere in that handoff, things get lost: interaction behaviors, edge cases, data states, design intent. A design prototype shows what a product looks like. A coded prototype shows what a product does. That difference matters more than most teams realize.
When you hand a developer a Figma file, they're getting a visual reference. When you hand a developer a coded prototype, they're getting a working system. The handoff gap shrinks dramatically. As AI tools reshape how teams research, design, and build products, a new approach is emerging: interactive prototypes created directly in code.
Users care about whether a feature works immediately and is tested in real action. That kind of design can't be proven in static files. Design isn't becoming less important, but it is changing. It now has to be validated in code, not just in Figma.
At Ballast Lane Applications, we've begun integrating this workflow into our product delivery process. Instead of handing off static design artifacts, teams can now deliver working prototypes that behave like real applications. These prototypes provide developers with a far more practical starting point while giving clients a clearer understanding of what they are approving. The result is a faster, more aligned path from concept to production.
The Limits of Traditional Design Prototypes
Design tools like Figma remain incredibly valuable for collaboration, visual exploration, and design systems. They allow teams to experiment with layouts, refine user interfaces, and create a consistent visual experience across all platforms. However, this has some limitations.
Most design prototypes are still simulations rather than functional systems. They illustrate interactions, but they do not execute real logic. Data is often static, and the system's behavior must still be interpreted and reimplemented by engineers.
This gap can create several challenges. Developers must translate visual designs into architecture and working features. Also, design intent can be interpreted differently when moving from mockups to code. As a result, teams are exploring ways to bring engineering workflows earlier into the design process. This gap becomes even more noticeable for complex digital products.
A New Workflow: From Idea to Interactive Prototype
AI development tools have made it possible to develop working prototypes quicker than ever before. Now, design and product teams can build interactive prototypes written directly in code, often within a matter of hours or days. These prototypes behave much closer to a real application because interfaces respond to user input, and these workflows can be tested as if they were part of a live system. This approach significantly reduces the distance between design intent and engineering implementation.
Why Developers Prefer Code-Based Prototypes
One of the most valuable outcomes of this approach is the impact on development teams. Previously, design handoffs often required engineers to interpret design intent and reconstruct functionality from static files. Even the most detailed prototypes can leave important questions unanswered.
In contrast, a coded prototype provides developers with something far more actionable. Instead of starting from a blank canvas, engineers receive a working reference. Here's how we recently implemented this strategy on a project.
The Role of AI and How It Is Helping in This Shift
AI tools are not replacing designers or engineers. Instead, they are helping them because teams can generate product specifications and test workflows earlier in the process. Rather than treating design and engineering as separate phases, the process becomes more collaborative; Designers can think more like engineers, and engineers receive more structured inputs earlier in the lifecycle.
When stakeholders interact with a working model of a product, discussions become far more productive. Instead of debating abstract ideas, teams can evaluate real behaviors and workflows. This leads to better product decisions earlier in the process. Clients gain confidence because they can see how a system will actually work. Development teams benefit because expectations are clearer, and product teams can refine features before committing significant engineering resources. Often, this approach can determine whether a project moves forward at all.
Building Better Products Together
At Ballast Lane Applications, we believe that strong products emerge from close collaboration between product, design, QA, and engineering teams. Interactive prototypes represent one way we continue to refine how those teams work together.
By combining the use of modern AI tools and disciplined engineering practices, we can move from early concepts to working solutions quickly and with greater confidence. Most importantly, we can give both our clients and our development teams a product they can actually experience.