Introduction

Application development has evolved significantly over the years, and I now feel confident in my understanding of how applications should be designed and implemented. One of the most fundamental decisions in software development is the approach taken—whether to start with the back-end or the front-end. While many developers emphasize back-end architecture first, I firmly believe that a front-end-first design is key to a successful product.

A front-end-first approach prioritizes the end user, enabling rapid iterative development and helping to define the data models before designing the underlying system. Too often, applications suffer from overly complex back-end structures that fail to meet user needs. By starting with the user interface and experience, developers ensure that they build a system that is both functional and intuitive.

The Pitfalls of Back-End-First Development

Many developers, often favoring technical complexity over usability, design systems that are bulky and difficult to navigate. This issue arises in two primary ways:

1. Data-Driven Complexity: Some applications are built with a strong focus on the data model first, forcing users to adapt to rigid structures instead of designing the system around user needs.
2. Legacy-Driven Constraints: Other applications attempt to fit new designs into existing data models, making them inflexible and difficult to iterate on.

Users naturally gravitate toward simple and easy-to-use applications, abandoning those that feel cumbersome. A prime example of this can be observed in the differences between CNBC’s web and mobile applications.

Case Study: CNBC’s Web vs. Mobile Application

CNBC, a leader in business news, has a robust web platform that allows users to search stock tickers and access company profiles. The website offers an extensive array of tools for professionals, including company performance metrics, related news, and investment analytics.

However, CNBC’s mobile application significantly limits these features. Due to mobile screen size constraints and the lack of physical input devices like a mouse and keyboard, the app offers a simplified experience. This demonstrates a fundamental truth in software development: the client experience drives design decisions. By prioritizing front-end usability, CNBC ensures that users on different platforms receive an optimized experience tailored to their needs.

A Personal Experience: The Downfall of Poorly Designed Systems

In a previous role, I worked on a decades-old development project called TRAB (Total Return Alpha Beta), a system designed to evaluate the Value-at-Risk (VaR) of financial portfolios. The application relied on a Monte Carlo simulation model incorporating correlation, volatility, and Brownian motion calculations to generate underlying price movements. However, the system suffered from:

• Poorly structured data models: The data was messy and difficult to navigate.
• Low usability: The interface was unintuitive, requiring developers to manually adjust SQL queries in management tools.
• Frequent bugs: Weekly errors required deep dives into hundreds of thousands of lines of code.
• Lack of stakeholder buy-in: The system did not effectively communicate its outputs to end users.

Had TRAB been designed with a front-end-first approach, its usability and adaptability would have vastly improved. The real issue wasn’t just the back-end—it was that we lacked a clear understanding of our inputs and outputs from the start. If we had begun by defining user interactions and expected results, our data architecture would have been far better structured, making the entire system more reliable and user-friendly. Instead, we ended up with a case of garbage in, garbage out.

The Solution: A Client-First, Front-End-First Approach

If I were to redevelop TRAB today, I would prioritize:

• A structured data mart for cleaner, more accessible data storage.
• Breaking up ETL processes into smaller, manageable services.
• An intuitive user interface that empowers portfolio managers, researchers, and developers to manipulate data without needing SQL expertise.
• A real-time data dashboard for monitoring simulation job status and VaR outputs.

A successful redesign would enable users to interact with the system efficiently, rather than relying on developers to extract insights manually.

The Communication Gap Between IT and Clients

One of the largest complaints internal IT teams face is a lack of communication with business stakeholders De Alermeida et al. (2015) . Too often, developers design systems in isolation, leading to delays, unmet expectations, and frustration. A front-end-first approach forces continuous client engagement because developers cannot proceed without defining what should appear on the screen. This leads to:

• Frequent feedback loops through in-person interactions and short conversations.
• Clearer expectations set during structured meetings.
• More user-centric solutions, preventing wasted development effort on unnecessary features.

Addressing Back-End Challenges in a Front-End-First Model

One concern with a front-end-first approach is that rapidly changing client requirements can stall back-end development or lead to codebase complexity. Three key strategies can mitigate these issues:

1. Flexible Data Models: During early prototyping, developers should avoid rigid schemas and premature data modeling. Instead of quickly defining strict types, developers should embrace flexibility with any, simple types (e.g., str, int, boolean), or JSON structures. This allows for greater adaptability as requirements evolve and ensures that data architecture is shaped by actual user interactions rather than assumptions. The back-end can be hard to codify until inputs and outputs are well understood, and resisting early constraints leads to a more natural and effective system design.
2. Industry-Specific Developer Expertise: Developers with domain knowledge can bridge the gap between business needs and technical implementation. My background in capital markets and investment products enables me to design applications which require a deep understanding of financial data.
3. Predefined Templates & Standards: Establishing agreed-upon data structures, and interface templates early in development helps streamline implementation and prevents repeated redesigns.

The Role of AI in Agile Development

Artificial intelligence and chatbots are revolutionizing software development. What once took me a week of developing and reading documentation now takes a single day. AI enables:

• Faster prototyping by generating code snippets based on natural language input.
• Improved documentation through automated summarization of project workflows.
• Enhanced stakeholder engagement by translating complex technical details into business-friendly insights.

While concerns about data privacy and model accuracy remain, organizations must adapt to leverage AI’s benefits or risk falling behind. Establishing robust legal frameworks with AI providers can help maintain security while enabling innovation.

Unlocking Data’s Full Potential

More than two-thirds of organizations underutilize their data, and only 22% trust their data (Dataversity 2024). Rather than constantly seeking new data sources, organizations should better leverage the data they already have. By applying a client-first approach, businesses can uncover valuable insights without unnecessary data expansion. Data governance and liberal access permissions are critical to empowering developers to extract meaningful stories from existing datasets.

The Future: "Spry" Development

The future of software development is nimble and hyper-agile. Many teams claim to use agile methodologies but fail to embrace their full potential. With the rise of NoSQL databases and AI-assisted development, we can move faster than ever before. I propose calling this new methodology "Spry" development—an evolution of agile that eliminates bureaucratic bloat and embraces rapid, iterative, and user-driven design.

Conclusion

Software development is entering a renaissance. By prioritizing front-end-first methodologies, embracing continuous client collaboration, and leveraging AI-driven efficiencies, we can create applications that are not only functional but also intuitive and adaptable. The days of rigid, back-end-driven design are fading. The future belongs to those who build with the user in mind first—and those who embrace "Spry" development will lead the charge.

References

Dataversity. (2024). Organizations are underutilizing their data: Here’s why and how to fix it. Retrieved from https://www.dataversity.net/organizations-are-underutilizing-their-data-heres-why-and-how-to-fix-it/?hl=en-US

De Alermeida, A. R., Medeiros, P. Y., & Halpern, E. E. (2015). Why internal clients are dissatisfied with the quality of information technology services provided by their organizations? Procedia Computer Science, 55, 922–930. https://doi.org/10.1016/j.procs.2015.07.112