Designing Greenfield Projects

Introduction

"The sooner you start to code, the longer the program will take."
-- Roy Carlson

Designing software is a complex process that requires a lot of thought and planning. There is a common misconception that we only need to design software when we are building something new. However, the design process is just as important when working on existing systems, it just looks quite different.

Regardless of whether you are working on a greenfield project, an existing system, or even responding to an interview question, jumping straight into coding without a plan is a recipe for disaster. The design process is crucial for ensuring that the software you build is maintainable, scalable, and meets the needs of your users.

Greenfield Projects

If you ask ten software engineers if they would rather work on a greenfield project or an existing system, all ten will probably say greenfield. Greenfield projects are exciting because you get to start from scratch and build something new. You aren't tied to the design decisions of the past, and you have the freedom to experiment with new technologies and patterns. However, greenfield projects also come with their own set of challenges.

Understanding the Problem

The biggest challenge of a greenfield project is understanding the problem you are trying to solve. This might seem obvious, but it is easy to get caught up in the excitement of building something new and lose sight of the needs of your users. There are two main reasons why this can be difficult:

• Users rarely know what they actually want. They might have a vague idea of what they need, but it is up to you to translate that into a concrete set of requirements.
• The problem itself might be complex and require a deep understanding of the domain in order to solve it.

You will never have a complete understanding of the problem at the beginning of a project. However, it is important to spend time talking to users, gathering requirements, and researching the domain in order to get as close as possible.

Requirements Gathering

Requirements gathering is the process of collecting and documenting the needs of your users. This is typically done through interviews, surveys, and observation. The goal is to understand what the users need the software to do, and what features are most important to them. The exact approach will vary depending on the project and how accessible the users are.

If you are building an internal tool for a small team, you might be able to sit down with each user individually and talk through their needs. When a question arises, you can just walk over and ask them directly.

When you are building a consumer-facing product, you might need to conduct surveys or focus groups in order to gather requirements. Requirements questions that come later in the project might be more difficult to answer, as the users might not be as accessible. You often have to rely on a product manager or customer support to act as a proxy for the users.

The most difficult case is when you are trying to offer something completely new. In this case, you might not have any users to talk to. You will need to rely on your own intuition and research to come up with a set of requirements. These end up as wishlists of features, which you hope will be validated by the users once the product is released.

Depending on the organization, requirements gathering might be done by a dedicated product manager, a business analyst, or the software engineer themselves. Regardless of who is responsible, it is important to involve the entire team in the process. This ensures that everyone has a shared understanding of the problem and can contribute to the solution.

Non-Functional Requirements

Non-functional requirements are where your skills as a software architect really come into play. These are the requirements that are not directly related to the functionality of the software, but are crucial for its success. Examples include:

• Security: How sensitive is the data that the software will be handling? What measures need to be taken to protect it?
• Performance: How fast does the software need to be? How many users does it need to support?
• Scalability: How easy is it to add new features or support more users?
• Maintainability: How easy is it to fix bugs or add new features?
• Usability: How easy is it for users to learn and use the software?
• Reliability: How often does the software need to be available? How quickly does it need to recover from failures?

Non-functional requirements are often overlooked simply because non-engineers don't know any better, but they are just as important as functional requirements. They can have a huge impact on the success of a project, and it is important to consider them from the beginning. These requirements will shape the architecture of the entire system and the technologies you choose to implement it.

The Designing for Non-functional Requirements section goes into more detail on how to design a system under these constraints.

Importance of Domain Knowledge

Domain knowledge is a critical, but often overlooked, aspect of effective software system design. Without a solid understanding of the problem space, it's easy to make poor design decisions that lead to unnecessary complexity, fragile assumptions, or features that don’t actually solve user needs. Domain knowledge allows you to model the system in a way that aligns with real-world concepts, user workflows, and business logic. It informs your choice of abstractions, guides boundaries between modules, and helps you prioritize what's important and what's not.

Moreover, good system design isn’t just about writing clean code—it’s about solving the right problem in the right way. Engineers who understand the domain can identify edge cases, anticipate future changes, and communicate more effectively with stakeholders. They can also spot inconsistencies or missing requirements early, reducing the risk of costly redesigns later. Ultimately, strong domain knowledge leads to software that is more intuitive, more maintainable, and more valuable to its users.

Decomposing the Problem

Once you have a clear understanding of the problem you're solving and the constraints you're operating within, the next step is to begin identifying the key components of your system and how they should be organized. Your goal at this stage is to define the overall structure of the system, what parts it consists of, how those parts interact, and how responsibility is distributed. This includes considering how events will be handled, how data will flow through the system, and what the deployment environment will look like. It's also essential to think about who will maintain and support the system over time, and how operational responsibilities will be managed.

Design is an inherently iterative process. You begin with a high-level view and refine it gradually, adding detail as your understanding deepens. Your design will evolve as you gather more information, encounter new constraints, or revisit previous assumptions. It’s important to keep your design documentation current and reflective of these changes, outdated designs quickly lose their value.

While the specifics of any software design depend on the problem domain, one universal principle is to isolate areas of uncertainty and design for change. Good designs create clear boundaries around parts of the system that are likely to evolve, allowing you to make changes without destabilizing the entire codebase. Flexibility and clarity are the hallmarks of robust system design.

Isolating Uncertainty

One of the most important principles in system design is to isolate uncertainty. Whenever you encounter an area in your design where the best approach is unclear, whether due to technical unknowns, changing requirements, or external dependencies, you should aim to encapsulate and decouple that part of the system. By doing so, you shield the rest of the system from potential volatility and make it easier to adapt to changes later.

For instance, if you’re uncertain about which type of database to use, you can define a clear interface that abstracts the database interactions from the rest of the application. This allows you to switch databases later without rewriting major portions of your codebase. Similarly, if you’re undecided about which cloud provider offers the best cost or features, you can abstract away provider-specific details behind a common interface. In both cases, isolating uncertainty gives you flexibility and reduces the cost of future changes.

Allowing for Change

At the beginning of any software project, you typically have the least amount of information about the problem, the constraints, and the real needs of users. As the project moves forward, your understanding deepens, new requirements emerge, priorities shift, and unforeseen challenges arise. A good design anticipates this uncertainty by making it easy to adapt and evolve the system over time.

To support change, your architecture should emphasize modularity and loose coupling. Each component should have a clear, focused responsibility and minimal dependencies on other parts of the system. This separation of concerns allows individual components to be updated, replaced, or extended with minimal impact on the rest of the codebase.

You can count on requirements changing, sometimes subtly, sometimes drastically. By designing a flexible, modular system from the outset, you give yourself the ability to adapt without needing to rebuild everything from scratch. This not only improves the system’s longevity, but also reduces technical debt and speeds up future development.

It's tempting to try to design a system that accounts for every possible future need, but this often leads to over-engineered, overly complex solutions that are difficult to understand and maintain. Instead, your goal should be to create a design that is adaptable, not all-encompassing. Focus on solving the current problem cleanly, while leaving room for extension. By keeping the design simple and modular, you make it easier to respond to change when it actually arrives, instead of guessing at future needs and building complexity prematurely. Adaptability is far more valuable than attempting to predict and implement every possible feature up front.

Communicating Your Design

At this stage, your design should remain relatively abstract, focusing on the high-level structure and organization of the system. You should have a clear understanding of the major components, how they interact, and the responsibilities each one holds. However, it’s equally important to be able to communicate this design effectively, whether to team members, stakeholders, or future maintainers.

Visual representations are often the fastest and most effective way to share and refine your design. Diagrams, flowcharts, and system architecture sketches help convey relationships, data flow, and system behavior more clearly than text alone. These visuals not only help others grasp your design quickly, but they also serve as a valuable tool for uncovering inconsistencies, hidden dependencies, or missing elements in your own thinking.

If your design is too abstract to explain, it may be too abstract to implement. Strive for a balance between conceptual clarity and practical detail. A well-structured design should be easy to explain at a high level without overwhelming others with complexity.

Finally, if you find it difficult to produce a clear, comprehensible diagram of your system, that may be a sign that your design is too tightly coupled or overly complex. A good design should naturally lend itself to simple, intuitive visualization. If it doesn’t, consider revisiting the structure to simplify or decouple the components.

Design Twice

Once you have a basic outline of your system design, it's important to resist the urge to dive directly into the implementation. One of the most valuable parts of the design process is exploring multiple alternatives. Different architectures, technologies, or structural approaches can offer trade-offs in complexity, performance, scalability, and maintainability. By considering several options, you give yourself the opportunity to discover simpler, more robust, or more elegant solutions than your initial idea.

Exploring alternatives doesn't mean starting from scratch every time, it means deliberately challenging your assumptions. Ask yourself: What if we reversed the flow of data? What if we used event-driven communication instead of REST APIs? What would change if this component were client-side instead of server-side? These questions help expose blind spots and force you to think critically about the problem, rather than defaulting to familiar patterns.

You can also use this phase to evaluate risks and uncertainties. If you're debating between two technologies or architectural styles, consider prototyping small pieces of each. This helps reduce uncertainty and gives you concrete data on which to base your decision. Even a few hours spent validating an idea can save days or weeks of rework down the line.

Finally, make sure to document the trade-offs of each option you consider, not just which design you chose, but why you chose it. This creates a record of your thinking that can help future maintainers understand the system, and it makes your reasoning more rigorous. Having a record of the alternatives you considered and the rationale behind your decisions can help to avoid duplicate effort in the future and can also serve as a valuable learning tool for you and your team.

Scope Creep

A common question that comes up when designing software is how to handle scope creep. Scope creep is when the requirements of a project change after the project has started. This can be a big problem because it can lead to delays and cost overruns.

Software engineers are frequently trying to find ways to prevent scope creep, either by setting boundaries, or through manager intervention. However, scope creep is a natural part of the software development process. It is impossible to predict every possible requirement at the beginning of a project, and as the project progresses, new requirements will emerge. In order for a project to be successful, it is important to be able to adapt to these changes.

Your objective as a software engineer is to design a system that is flexible enough to handle these changes. This means that you need to be able to add new features without breaking existing functionality. This is where good design comes in. Your system should be flexible and modular, so that you can add new features without having to rewrite large parts of the codebase.

Evaluating Your Design Choices

Once you've developed a potential design, or a few competing alternatives, the next critical step is to evaluate those choices rigorously. Good design isn’t just about making things work, it’s about making informed, thoughtful decisions that balance trade-offs and serve long-term goals. Evaluation helps ensure that your design is not only correct, but effective, adaptable, and sustainable.

Start by revisiting your requirements. Ask whether the design clearly satisfies both the functional and non-functional requirements. Does it support the intended use cases? Will it perform under expected loads? Is it secure, maintainable, and resilient? It's easy to overlook constraints or edge cases once you’ve grown attached to a particular solution, so actively look for ways your design might fail.

Assess modularity and separation of concerns. A strong design should decompose the system into well-defined components with clear responsibilities. Evaluate how tightly coupled your components are. Can changes in one module be made independently of others? Loose coupling and high cohesion are often indicators of a design that will be easier to extend and maintain.

Identify points of inflexibility and risk. Consider which parts of the system are likely to change and how difficult those changes will be. Does your design isolate areas of uncertainty or allow for easy substitution of components (e.g., databases, APIs, third-party services)? Are there single points of failure or assumptions that might break in the future?

Solicit feedback. One of the best ways to evaluate a design is to walk others through it. Whether it’s through informal discussions, design reviews, or pair sessions, explaining your choices can reveal assumptions you didn’t realize you were making. Others may spot problems or suggest simplifications you hadn’t considered. Even if you disagree with their suggestions, the process of articulating your design can help clarify your own thinking and expose weaknesses in your reasoning.

Use simple metrics if appropriate. While subjective judgment plays a key role, you can also use lightweight metrics to guide evaluation. For instance, count the number of responsibilities per module, measure the depth of dependencies, or look at how many modules are affected by a typical change. These metrics won’t give you all the answers, but they can highlight areas worth closer inspection.

Ultimately, evaluating a design is about being honest with yourself. Challenge your assumptions, look for failure points, and think beyond the initial implementation. A little extra scrutiny up front can prevent significant pain down the line.

Common Design Pitfalls

Even experienced engineers can fall into common traps during the software design process. Being aware of these pitfalls can help you recognize and avoid them early:

1. Premature Optimization Focusing on performance or scalability too early can lead to over-engineered and unnecessarily complex systems. Optimize only after you’ve validated that a problem actually exists and affects your goals.

2. Over-engineering Trying to design for every possible future use case often leads to bloated, inflexible systems. Favor simplicity and adaptability over trying to anticipate every need. Build for change, not for vague possibilities.

3. Tight Coupling Systems where components are overly dependent on each other become fragile and hard to maintain. Changes in one area ripple through others. Strive for loose coupling and clear interfaces.

4. Ambiguous Responsibilities When components or modules do too much or overlap in purpose, systems become harder to understand and modify. Follow the principle of single responsibility and define clear boundaries.

5. Ignoring Non-Functional Requirements Focusing only on "what the system does" and not "how well it does it" can lead to systems that are hard to scale, secure, or maintain. Non-functional requirements should shape your architecture from the beginning.

6. Lack of Design Communication A design that lives only in one person’s head, or in a disorganized document, isn’t useful to a team. Use diagrams, documentation, and clear explanations to make your design accessible and shareable.

Things to Keep in Mind

A few closing points to keep in mind as you move forward with your design process:

Up Front vs Emergent Design

It’s tempting to try to make all of your most important design decisions upfront, aiming to build the system right from the very beginning. However, this approach, commonly associated with the waterfall method, has consistently proven ineffective for all but the most trivial software systems.

At the start of a project, you know the least about the system you’re building. Requirements are often incomplete or evolving, constraints may not yet be clear, and trade-offs remain uncertain. It’s impossible to make all the right decisions upfront. Worse, the earliest decisions tend to be the most expensive to change. By the time flaws in the design become apparent, the system is usually so tightly coupled to that design that making significant changes becomes costly and difficult.

On the other end of the spectrum is the emergent design approach, often promoted by Agile advocates who may misinterpret the Agile Manifesto. This approach avoids upfront design altogether, developers start coding immediately and let the design emerge incrementally. While this method allows flexibility and adaptation to changing requirements, it often leads to poorly structured systems if not carefully managed. It requires constant vigilance: regularly reviewing the design and refactoring code to improve it as understanding deepens.

The biggest challenge with purely emergent design is that some decisions, especially those related to security, scalability, and performance, are too foundational to be added or fixed later without major rewrites. Building on a flawed foundation can mean discarding substantial work to correct course.

In practice, the best results come from blending these two approaches. Make thoughtful, foundational design decisions early on, but remain open and ready to revise them as you gain new insights. Continuously evaluate and refine your design throughout development, embracing refactoring whenever you see an opportunity to improve. This balance helps create software that is both robust from the start and adaptable over time.

Minimum Viable Architecture

When starting work on a new system, it’s best to begin with a minimum viable architecture, the simplest architecture that can support building the system you need. Begin with a straightforward design and evolve it incrementally, making design decisions as you gain a deeper understanding of the requirements and constraints. Continuously refactor your code to improve the architecture as the system grows.

This approach is especially critical for startups and organizations developing new products, where requirements, constraints, and trade-offs are often unclear or rapidly changing. Since you can’t anticipate every need upfront, starting simple allows you to adapt efficiently and avoid unnecessary complexity.

A common pitfall is for startups to prematurely adopt complex architectures like microservices simply because they believe it’s the right or modern approach. Without clear requirements or constraints justifying such complexity, this often leads to an over-engineered system that is harder to build, maintain, and evolve. In most cases, starting with a monolithic architecture and gradually evolving it as the product matures is a more practical and effective strategy.

Know When to Compromise

In software design, trade-offs are inevitable. There is no such thing as a perfect design, only choices that optimize for certain priorities at the expense of others. Whether it's performance versus readability, flexibility versus simplicity, or speed of delivery versus long-term maintainability, every decision involves a balancing act.

The most important skill in navigating these trade-offs is judgment. This begins with a clear understanding of your system’s goals and constraints: What does success look like? What risks are acceptable? What is likely to change, and what is not? Without a firm grasp of these fundamentals, it's easy to make compromises that appear convenient in the short term but cause significant harm over time.

Not all compromises are bad. In fact, some are necessary and pragmatic. For example, choosing a less elegant solution that allows you to meet a critical deadline may be justified, but only if the trade-off is acknowledged and planned for. Similarly, simplifying a design to ease onboarding for new developers can be a wise choice, even if it sacrifices some technical purity.

The danger lies in compromises that are made blindly or out of habit. Cutting corners on test coverage, ignoring clear abstractions, or introducing tightly coupled components to “just make it work” may seem harmless at first. But these decisions accumulate, creating technical debt that can cripple a project over time.

Good software engineers recognize that compromise is not a failure, it’s a strategic decision. The goal is not to eliminate all trade-offs, but to make them consciously, with full awareness of their impact. Communicate these decisions with your team, document the rationale, and revisit them as the system evolves. A compromise made today may no longer make sense tomorrow.

Know When to Skip Design

In some situations, the best design choice is minimal, or even no formal design at all. For small, self-contained projects or early-stage prototypes, it may not be worth investing heavily in architectural planning. If you're building a quick proof of concept, an internal tool with a short lifespan, or running an experiment to validate an idea, the priority is often speed and feedback, not long-term maintainability.

In these cases, it's often acceptable to write code quickly and iterate as you go. The goal is to move fast, test assumptions, and explore possibilities. The cost of over-engineering something that may never be used in production can outweigh the benefits of a robust design.

That said, "no design" should not mean "no discipline." Even temporary or throwaway code benefits from clarity, organization, and basic structure. Avoid writing code that is overly coupled, obscure, or brittle, it may live longer than you expect, or become the foundation for future work. Use simple, modular patterns, name things clearly, and isolate concerns where it’s easy to do so.

Nothing is more permanent than a temporary solution.

These fast-path projects are exceptions, not the rule. Prioritizing short-term speed over long-term quality can be appropriate, but only in special circumstances. If you regularly find yourself skipping design because “it’s faster,” it may be time to step back and re-evaluate your development practices. Over time, this mindset leads to fragile, unmaintainable systems—even in places where robustness matters.

Conclusion

The software design process is not about creating perfect blueprints, it's about making informed, thoughtful decisions that guide implementation, support future changes, and enable collaboration. Good design balances structure with flexibility, and precision with clarity. It’s an ongoing process of learning, communicating, and adapting as the problem and constraints evolve.

At its core, software design is about managing complexity so that the system remains understandable, maintainable, and extensible. A well-designed system doesn’t just work, it makes it easy for others to build on, troubleshoot, and adapt over time. That’s what separates quick hacks from enduring software.

As you move from concept to code, remember that the best designs are not necessarily the most clever or sophisticated, but the ones that make it easiest for others (and your future self) to keep the system alive and healthy. Design like you won’t be the one maintaining it, because eventually, you won’t be.

Image Credits

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