Building Software That Actually Works: An Engineer's Guide to Requirements-First Development

Most software projects fail not because of technical complexity, but because teams build the wrong thing. Despite advances in frameworks, methodologies, and development tools, the fundamental challenge remains unchanged: how do you ensure you're solving the right problem?

This guide presents a different approach to software development—one where engineers take ownership of understanding business context and defining clear requirements before writing a single line of code. The insights come from an unconventional career path that spans addiction therapy, scientific writing, customer success, and software engineering. This unique combination revealed patterns that traditional engineering education often misses.

What You'll Learn

The following sections will show you how to transform your approach to software development by putting requirements first. You'll discover why the traditional handoff model fails, learn a systematic process for gathering and maintaining requirements, and understand how this approach leads to better technical decisions and more successful projects.

Section 1 explores how experiences outside traditional engineering roles provide crucial insights into building software that actually works. These lessons reveal why most project failures stem from context problems, not technical problems.

Section 2 challenges the conventional wisdom that engineers should focus only on technical implementation. You'll see why engineers are uniquely positioned to own more of the product definition process and how this approach improves both business outcomes and job satisfaction.

Section 3 provides a practical, step-by-step methodology for implementing requirements-first development. Based on the proven Volere framework, this process helps you understand business context, identify all stakeholders, and map business needs to technical solutions.

Why This Matters Now

In an era of rapid development cycles and increasing complexity, the temptation to skip requirements gathering grows stronger. Agile methodologies often discourage upfront planning. Modern tools make it easier to build and iterate quickly. But speed without direction leads to waste.

This guide argues for a middle path: thorough requirements gathering that establishes clear context, followed by iterative development that maintains alignment between business needs and technical implementation. The result is software that solves real problems efficiently and systems that evolve gracefully as business needs change.

The principles apply whether you're building internal tools, customer-facing products, or complex system integrations. The scale doesn't matter—the fundamental challenge of understanding what to build remains constant.

Section 1: My Unconventional Path to This Perspective

Most software engineers follow a predictable career path. They study computer science, maybe pick up some internships, then jump into coding roles. My journey looked nothing like that—and those detours taught me something crucial about building software that actually works.

I started as an addiction therapist. This meant spending my days understanding complex human problems, breaking them down into manageable pieces, and creating systems that helped people change their behavior. Every day, I had to figure out what people actually needed versus what they said they needed. I learned to ask better questions and listen for the real problem hiding behind the obvious symptoms.

From therapy, I moved into technical and scientific writing. This role was different from typical tech writing—I analyzed data from field readings and provided insights to customers who needed to understand what that data meant for their operations. My boss, a Stanford-educated geophysicist who taught writing classes at the University of Denver, taught me how to structure complex information so readers could follow the logic without getting lost.

This writing experience revealed something important about communication. Most failures happen because writers organize information for their own convenience, not the reader's needs. Technical teams often present solutions before explaining the problem. They bury important decisions in jargon. They assume readers share their context. These habits create confusion even when the underlying ideas are sound.

Next came customer success, but in a specialized role. I was the "web services liaison," which meant I worked with customers who were integrating our product programmatically into their systems. This forced me to learn complex system integrations like SAS and various web services protocols. I wasn't just handling complaints—I was solving technical integration problems in real-time while customers waited on the phone.

This role put me on the front lines when software didn't work the way people expected. I saw the same problems repeatedly: software that solved the wrong problem, APIs that made sense to engineers but confused users, and systems that worked perfectly in isolation but failed when integrated with real-world workflows.

Finally, I became a software engineer. But I brought all those previous experiences with me.

This combination gave me six key insights that most engineers never develop:

First insight: People resist change, even when it leads to better outcomes. Status quo feels safe. Most organizations have people more concerned with keeping their jobs easy than building better results. This isn't criticism—it's human nature. But it means "bigger must be better" thinking often wins, even when small, targeted solutions would work better.

Second insight: Neither social systems nor engineered systems behave the way you expect. Teams accidentally compete with each other. Different groups solve similar problems in completely different ways. Office cultures vary dramatically between floors of the same building. Feedback loops create surprising effects. You can't predict how systems will actually work just by looking at how they're supposed to work.

Third insight: We don't ask "what will change?" when building systems. Designing for known, static requirements would be easy. But that's not our job. We design for unknown, dynamic systems that will evolve in ways we can't predict. This requires building flexibility into the foundation, not just the features.

Fourth insight: New ideas need repetition to take hold. You must repeat yourself often. You must say the same things in different ways to different people. Take your maximum tolerance for repetition, double it, and you might be starting to repeat yourself enough. This isn't because people are slow to understand—it's because organizational momentum requires sustained pressure to change direction.

Fifth insight: You can only work with existing feedback loops or try to cancel them out. Creating entirely new feedback loops in established systems takes years. Smart engineers learn to identify the feedback loops that already exist and figure out how to redirect them toward better outcomes.

Sixth insight: Context determines everything. The same technical solution can succeed brilliantly in one environment and fail completely in another. Understanding the business context, the team dynamics, and the organizational pressures is just as important as understanding the code.

These insights changed how I approach software engineering. I realized that most project failures aren't technical failures—they're context failures. We build the wrong thing because we don't understand what we're actually trying to solve. We create elegant solutions that nobody wants because we never figured out what people actually need.

This realization led me to a controversial conclusion: engineers should own much more of the product definition process than traditional wisdom suggests.

Section 2: Why Engineers Should Own More Product Definition

Traditional software organizations split responsibilities cleanly. Business professionals handle market research, product strategy, and requirements gathering. Engineers focus on technical implementation. Product managers serve as translators between the two groups. This division of labor seems logical, but it creates a fundamental problem: context gets lost in translation.

Here's what typically happens. Business stakeholders identify a need and create high-level requirements. Product managers translate these into user stories. Engineers receive these stories and build what they think is being requested. The final product technically meets the specifications but fails to solve the actual business problem. Everyone did their job correctly, yet the project fails.

I've seen this pattern repeatedly. A marketing team requests "better analytics dashboards." Product management creates stories about charts and filters. Engineers build a technically impressive dashboard with every feature requested. But the marketing team still can't answer their core question: which campaigns actually drive revenue? The solution met every requirement but missed the real need.

This happens because each handoff strips away context. Business stakeholders understand the problem deeply but struggle to articulate technical constraints. Product managers understand user experience but may miss technical nuances. Engineers understand implementation details but lose sight of business objectives. Information degrades with each translation.

The alternative approach challenges conventional wisdom: engineers should own much more of the product definition process. This doesn't mean every engineer becomes a product manager. Instead, it means engineers develop the skills to understand business context, identify real requirements, and design solutions that actually solve problems.

This approach works because engineers possess natural advantages for product definition. We think in systems and patterns. We excel at breaking complex problems into manageable pieces. We understand constraints and tradeoffs. These same skills that make us effective at technical problem-solving apply directly to product definition.

Consider the difference in outcomes. When engineers understand the business context, they make better technical decisions. They choose architectures that support business flexibility. They identify edge cases that matter to users. They push back on requirements that create technical debt without business value. They suggest alternative approaches that achieve business goals more efficiently.

My most successful projects followed this pattern. I spent significant time upfront understanding the business context, identifying all stakeholders, and mapping their actual needs. This investment paid dividends throughout development. Technical decisions aligned with business priorities. Feature implementations solved real problems. The final products required minimal changes because they addressed the right needs from the beginning.

The traditional objection is that engineers lack business skills. This contains some truth but misses the larger point. Most business skills can be learned. Understanding stakeholder needs, analyzing market context, and defining requirements are teachable skills. Engineers already possess the analytical thinking required for these tasks.

The bigger barrier is organizational inertia. Established companies have existing processes and defined roles. Changing these patterns requires sustained effort and management support. People resist new approaches even when they produce better results. Status quo feels safer than experimentation.

But the benefits justify the effort. Engineer-driven product definition reduces project failures, improves technical decisions, and creates better alignment between business needs and technical solutions. Teams move faster because they spend less time on miscommunication and rework. Products ship with fewer gaps between what was requested and what was actually needed.

This approach also makes engineering work more satisfying. Instead of implementing requirements that seem arbitrary, engineers understand how their work contributes to business success. They can suggest improvements and push back on poor decisions. They become true partners in product development rather than just implementers of other people's ideas.

The process requires new skills and different thinking, but the foundation already exists. Engineers who understand systems thinking can learn business analysis. Engineers who debug complex problems can identify user needs. Engineers who design elegant solutions can create effective requirements processes.

So how do you actually implement this approach? How do you move from traditional handoff-driven development to engineer-owned product definition? The answer lies in adopting a systematic requirements process that engineers can learn and apply.

Section 3: The Requirements-First Engineering Process

Most engineering teams start projects by jumping straight into technical discussions. What framework should we use? How do we structure the database? What's our deployment strategy? These questions matter, but asking them first creates a fundamental problem: you're designing solutions before you understand the problem.

The requirements-first approach flips this sequence. You invest significant time upfront understanding exactly what you're building and why. This isn't about creating lengthy documents that nobody reads. It's about establishing clear context that guides every technical decision throughout the project.

The Volere Framework: Your Methodology Foundation

After years of project failures and successes, I found the most practical guidance in an unexpected place: a business analysis textbook called "Mastering the Requirements Process." The authors created something called the Volere Requirements Specification Template. This framework gives you a systematic way to understand and document what you're actually building.

The Volere approach works because it addresses the root cause of most project failures: unclear requirements. But it goes deeper than typical requirements gathering. It forces you to understand the business context, identify all stakeholders, and map relationships between business needs and technical solutions.

Here's how the process works in practice.

Step 1: Establish Context Before Requirements

Traditional requirements gathering starts with features. "We need user authentication" or "We need real-time dashboards." But features only make sense within context. The Volere framework requires you to establish context first.

You begin by defining the project purpose and goals. This sounds simple, but most teams skip this step. They assume everyone shares the same understanding of why the project exists. This assumption creates problems later when stakeholders have different expectations about success.

Next, you identify all stakeholders. Not just users, but everyone who affects or gets affected by the project. This includes obvious groups like end users and business sponsors. But it also includes less obvious stakeholders like compliance teams, support staff, and integration partners. Each stakeholder group has different needs and constraints.

Then you identify project constraints. Budget and timeline constraints are obvious. But technical constraints matter too. What systems must you integrate with? What security requirements must you meet? What performance standards apply? Understanding constraints upfront prevents painful discoveries later.

You also define naming conventions, terms, and definitions. This prevents miscommunication. When someone says "user," do they mean end customer, internal employee, or system administrator? When they say "real-time," do they mean within milliseconds or within minutes? Clear definitions prevent confusion.

Finally, you document facts and assumptions. Facts are things you know for certain. Assumptions are things you believe but haven't verified. Identifying assumptions early saves enormous effort. Many project complications trace back to invalid assumptions that nobody questioned.

Step 2: Define Scope Before Features

Only after establishing context do you define scope. Scope has two parts: work scope and product scope.

Work scope describes the current situation and what you plan to change. What problems exist today? What processes need improvement? What business use cases must you address? This creates shared understanding of the starting point and desired end state.

Product scope describes how your solution fits into the larger business context. What other systems will integrate with your product? What workflows will change? What new capabilities will become possible? This prevents building isolated solutions that don't connect to real business needs.

Step 3: Map Business Use Cases to Product Requirements

Here's where engineering thinking becomes powerful. You map business use cases to product use cases, then product use cases to technical implementation. This creates clear traceability from business need to technical feature.

Business use cases describe what people need to accomplish in the real world. "Marketing team needs to identify which campaigns drive revenue." Product use cases describe how your system enables those accomplishments. "Marketing team can filter analytics by campaign and view revenue attribution." Technical requirements describe how you implement the product use cases.

This mapping process reveals gaps and conflicts early. You might discover that a requested feature doesn't map to any business use case. Or you might find that multiple business use cases require conflicting technical approaches. Resolving these issues during requirements gathering costs much less than fixing them during development.

Step 4: Distinguish Functional from Non-Functional Requirements

The Volere process categorizes requirements into functional and non-functional types. Functional requirements describe what the system does—its features and capabilities. Non-functional requirements describe how the system behaves—its performance, security, and reliability characteristics.

Most engineering teams handle functional requirements reasonably well. They understand features and can implement them. But non-functional requirements often get neglected until problems occur. I once witnessed a production system fail during a client load test because nobody had defined performance requirements. That failure was expensive and embarrassing.

Non-functional requirements need the same rigor as functional requirements. Instead of saying "the system should be fast," specify "the system must respond to user queries within 200 milliseconds under normal load." Instead of saying "the system should be secure," define specific security controls and compliance requirements.

Step 5: Build, Test, Refine, Repeat

Requirements aren't static documents. They're living specifications that evolve with your understanding. The Volere process includes what the authors call "trawling for knowledge"—continuously updating requirements as you learn more about the problem space.

This is where engineering thinking really shines. Software engineers understand iterative development. You build something, test it, learn from the results, and improve the next version. The same approach applies to requirements. You document initial requirements, prototype solutions, gather feedback, and refine your understanding.

The key difference from traditional development is keeping requirements and implementation synchronized. When you discover that a requirement is impractical, you update the requirement document, not just the code. When stakeholders request changes, you evaluate the impact on both requirements and implementation.

Practical Implementation: Start Small

You don't need to adopt the full Volere process immediately. Start with one project and focus on the context-setting steps. Define project purpose clearly. Identify all stakeholders. Document key assumptions. Map business use cases to technical features.

Pay special attention to non-functional requirements. Define specific performance targets. Identify security constraints. Specify reliability expectations. Test these requirements throughout development, not just at the end.

Use the requirements document as a communication tool. Share it with stakeholders and gather feedback. Update it when you learn new information. Keep it current throughout the project lifecycle.

The Payoff: Better Projects, Better Outcomes

This process requires more upfront investment than traditional development approaches. You'll spend more time in planning phases. You'll have more documents to maintain. You'll need to learn new skills beyond coding.

But the payoff justifies the investment. Projects that start with clear requirements finish faster and with fewer defects. Technical decisions align with business objectives. Stakeholder expectations match delivered results. Teams spend less time on rework and miscommunication.

Perhaps most importantly, this approach makes engineering work more satisfying. You understand how your technical decisions affect business success. You can push back on poor requirements with confidence. You become a true partner in product development rather than just an implementer of other people's ideas.

The requirements-first approach transforms how you think about software engineering. Instead of building systems that technically work, you build solutions that actually solve problems. And that makes all the difference.

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