You can spend months building software, hire experienced developers, and end up with an application that functions exactly as designed. But what happens when customers don’t want to use it?
That’s one of the most important software development mistakes to avoid: assuming that a technically functional application is also a product customers need.
Ghazenfer Mansoor, Founder and CEO of Technology Rivers, learned this through his own experience developing a SaaS startup. During a conversation with Todd Merrill on Tales from the Sky Lounge, he discussed what went wrong, how his approach changed, and why decisions made before and during development can determine whether a software investment delivers value.
His experience points to six areas where founders can make costly mistakes: failing to understand users, starting without clear requirements, choosing technology too early, neglecting code maintenance, overlooking security, and hiring the wrong expertise.
Software Development Mistakes to Avoid: Building Without Understanding Users
When Ghazenfer first started building his recruitment software business, he approached the project as an engineer. His focus was on developing a technically strong application, believing that a well-built product would naturally attract customers.
That didn’t happen.
Building software that works doesn’t mean you’ve built something customers want.
The application worked. But after all the effort that went into building it, customers still weren’t coming.
Ghazenfer realized that building a successful product required more than engineering expertise. He needed to understand how customers worked, where the existing process fell short, and what would give them a reason to use his software.
Over roughly two years, he learned more about product development and user experience, revisited the application’s approach, and made changes that eventually helped attract customers.
This is a problem that can easily arise in healthcare applications.
Imagine building a scheduling platform for a medical practice. Patients can book appointments, receive reminders, and view their upcoming visits. From a development perspective, everything works.
But what if the practice’s scheduling team still needs to manually update appointments in another system? What if patients struggle to find the right appointment type? Or the booking process doesn’t account for how different providers manage their availability?
The application may work as designed, but the practice still has to manage scheduling manually, and patients may continue struggling to book appointments.
That’s why it’s important to understand how people actually work before investing heavily in features. Where do they get stuck? What slows them down? And what would make their work easier?
These questions are part of effective product strategy and planning. The objective is to understand the problem well enough to build software that solves it, rather than simply delivering a collection of requested features.
Ghazenfer’s experience also shows why product decisions shouldn’t be treated as final once development begins. Feedback can reveal assumptions that need to change.
But those lessons only help when they’re translated into requirements the development team can act on.
Starting Development Before You Know What You’re Building
Even when you understand the user’s problem, a promising idea isn’t yet a development plan.
An application that connects patients with providers or accepts payments can involve dozens of decisions that aren’t obvious in an initial description.
During the podcast, Ghazenfer described clients approaching Technology Rivers with an idea written on a piece of paper or explained during an initial conversation. They know what they want to achieve, but many of the decisions required to build it haven’t been made yet.
He compared this to constructing a house.
You might know you want a large home with several bedrooms, but a contractor still needs to understand the layout, materials, dimensions, and budget. Without those details, neither the cost nor the finished result is clear.
Software development works similarly.
For an application that lets patients schedule appointments and pay for services, the team needs answers to questions such as:
- Does every provider have a separate calendar?
- Can patients reschedule without contacting the office?
- What happens when an appointment is canceled?
- Will payments be processed by credit card, ACH, or both?
These may seem like implementation details, but they can change the project’s scope considerably.
For example, accepting payments isn’t simply a matter of adding a payment button. The team may need to account for transaction processing, refunds, payment failures, user permissions, and integrations with financial systems.
If these requirements aren’t discussed until development is underway, founders may find themselves facing additional costs, changing timelines, and difficult decisions about which features they can still afford to build.
Ghazenfer explained how Technology Rivers uses its Blueprint Process to define what the application needs to do, how users will move through it, and which features belong in the initial development scope.
The purpose isn’t to create a rigid plan that can never change. It’s to establish enough direction that the team understands what it’s building and the business understands what it’s paying for.
Agile development leaves room to refine the product as the team learns. It doesn’t remove the need to agree on priorities, understand dependencies, or establish an initial scope.
A useful software development blueprint can help turn an idea into a more concrete plan while leaving room for changes as the product evolves.
The goal isn’t to document every future feature. It’s to define the initial requirements clearly enough to make more informed estimates of development costs and timelines, assign responsibilities, and select technology based on what the application actually needs.
Have a software idea but need a clearer development plan?
Before committing to development, it’s worth clarifying what your application needs to do, which features matter most, and what belongs in the initial scope. Learn how Technology Rivers approaches product planning and development.
Explore Our Product Development Services
Choosing Technology Before Understanding the Product
Once a business decides to build software, the conversation often moves quickly toward technology.
Should the application use Python? React? Node.js? Should it be a native mobile app or a cross-platform application?
Those questions matter, but Ghazenfer shared an example that illustrates why they shouldn’t always come first.
A client approached his team convinced that her application needed to be developed in Python.
When Ghazenfer asked why, the explanation wasn’t based on the application’s architecture, integrations, or business requirements. Someone had previously created a prototype using Python, so she assumed the final product should use it too.
The prototype had influenced the technology decision before the broader requirements were properly evaluated.
It’s an understandable assumption, particularly when you’re relying on technical recommendations from people who have already worked on your idea.
But the technology used to demonstrate a concept isn’t automatically the best choice for developing and maintaining the complete application.
Consider a healthcare business planning a platform that connects patients, providers, and administrative staff.
The system might need to connect with an electronic health record (EHR) system, support mobile access for patients, manage separate permissions for clinicians and administrative staff, or integrate with a payment processor.
Those requirements should influence the technology and architecture decisions.
A development team should also consider how easy the application will be to maintain, whether the chosen technologies can support the expected number of users and performance demands, and whether future developers can reasonably support them.
You don’t need to understand every programming language to evaluate a technology recommendation. Ask your development team how its proposed approach supports integrations, anticipated user volume, performance, maintenance, and future changes. A useful answer should also explain the tradeoffs, including whether a simpler or less expensive option could meet the same requirements.
If the team can’t explain why a technology makes sense for your product, it’s worth asking more questions before committing to it.
Ghazenfer’s example illustrates a broader point: knowing what technology you want isn’t the same as knowing what your product needs.
Choosing the right technology is only the beginning. Even a suitable stack can become costly if the code is difficult to maintain, making future updates and integrations harder than they need to be.
AI Can Build Faster, but Who Maintains What It Builds?
AI has changed how quickly developers can write code, generate interfaces, and experiment with new functionality.
For a business trying to validate an idea or accelerate development, that’s a meaningful opportunity. AI tools can help developers generate initial code, create interfaces, and test ideas without writing every component from scratch.
But faster development doesn’t automatically produce a codebase that’s easier to maintain.
During the podcast, Ghazenfer discussed how Technology Rivers uses AI tools in its development processes, alongside reusable components and established development practices.
One concern he raised was consistency.
When different developers work on the same application, they may approach similar problems in different ways. AI-generated code can introduce further variation if the team doesn’t have shared standards.
Ghazenfer warned that when developers follow different approaches without shared standards, maintaining the application becomes increasingly difficult as the team grows.
An application becomes harder to maintain when similar features are implemented inconsistently or developers struggle to understand how different components fit together. Reusable components and shared coding standards give teams established patterns to follow, while code reviews help maintain consistency.
These challenges become more noticeable as an application grows.
Imagine using an AI development tool to create a healthcare portal. You generate a dashboard, add appointment scheduling, connect a database, and produce a working demonstration.
Everything appears to function.
But once the application needs to support real users, additional questions emerge.
- Do similar features follow consistent coding patterns?
- What happens when an integration fails?
- Can developers trace a problem across different parts of the application?
- Could updating the appointment scheduling feature unexpectedly affect patient reminders or calendar availability?
These aren’t reasons to avoid AI-assisted development. They’re reasons to evaluate the software beyond what it can demonstrate.
Testing, code review, documentation, and architecture still matter. These considerations become especially important when moving from an AI-generated prototype to software intended for real users.
Our article on taking AI-generated applications from idea to production explores the engineering decisions involved, including how to evaluate what can be maintained, improved, or rebuilt.
Code ownership matters too: a business needs to know who controls the source code and whether another team could maintain it if necessary.
AI can help teams build faster, but without sound engineering practices, developers may spend additional time untangling inconsistent code, fixing unexpected problems, or updating features that were supposed to be easy to change.
And when an application handles sensitive information, maintainability is only part of the responsibility: the product must also be designed to limit inappropriate access.
Overlooking Security Until the Application Is Ready to Launch
Imagine a healthcare employee using a mobile application to review patient information.
They finish their work, put the phone down, and walk away. The application is still open, and sensitive information remains visible.
Someone else picks up the device.
What can that person access?
Ghazenfer raised a similar scenario during the podcast while discussing mobile application development and healthcare security.
It’s a simple example, but it illustrates why security needs to be considered as part of the application’s design rather than something added shortly before launch.
A healthcare application may have a login screen, encrypted communication, and role-based permissions. Those safeguards are important, but they don’t automatically address every way sensitive information could be exposed.
For example, what happens when a user leaves the application inactive? Does the session eventually expire? Are users required to authenticate again before accessing particularly sensitive information? Could patient details remain visible when the application is minimized or the device changes hands?
The safeguards a healthcare application needs depend on the patient information it handles, who is authorized to access that information, and how the application is used.
When an application handles protected health information, these decisions may also affect how the organization meets applicable HIPAA requirements.
Leaving a phone unattended doesn’t automatically mean a HIPAA violation has occurred. That depends on the circumstances and the safeguards in place.
Still, the example shows how leaving patient information visible in an inactive session could allow someone else using the device to see it.
A development team building healthcare software may need to consider authentication, session management, access controls, encryption, logging, secure data storage, and the responsibilities of third-party service providers.
Those requirements can affect architecture, development effort, testing, and ongoing operations.
Addressing these risks early makes it easier to design appropriate safeguards rather than trying to add security shortly before launch.
Planning a healthcare application that handles patient information? Explore our free HIPAA-focused development checklist for security and compliance considerations to discuss with your team. Enter your details to receive the guide by email.
Hiring Developers Before Knowing What Expertise You Need
Understanding users, planning requirements, selecting technology, and managing security all depend on having the right expertise at the right time.
Yet businesses sometimes know an application isn’t working without knowing which specialist can solve the problem.
Ghazenfer shared an example of a client who approached Technology Rivers looking for a UI designer.
The request seemed reasonable. The company wanted to improve its application, and design appeared to be the issue.
But after discussing the problem, Ghazenfer’s team realized that what the client actually needed was user experience expertise.
The difference matters.
| UI design | UX design |
|---|---|
| Focuses on the visual elements people interact with, such as buttons, layouts, and presentation. | Looks more broadly at how people use the application, navigate between tasks, and complete the workflows the product is supposed to support. |
The two disciplines overlap, but they don’t solve exactly the same problems.
If users are struggling because an application requires too many steps to complete a task, improving its appearance may not address the underlying issue.
The same misunderstanding can happen when businesses hire developers.
You may believe you need someone who knows a particular programming language, when the more immediate challenge is defining the product’s architecture or understanding how different systems should work together.
Or you may hire additional developers to accelerate a project, only to discover that unclear requirements are preventing the existing team from making meaningful progress.
In those situations, founders can end up paying for a larger development team while the same problems continue to slow the project down.
This is why choosing a development partner should involve more than reviewing technical skills and hourly rates.
Before agreeing to a development engagement, ask how the team will assess your requirements, any existing software, and technical constraints, what information it needs from you, and how it will explain its recommendations.
Their answers can help you judge whether they’re investigating the problem or simply proposing a team before understanding the work.
The right expertise depends on what’s holding the project back. Confusing user workflows may call for UX design, unreliable integrations may require software architecture expertise, and recurring defects may point to a need for stronger testing and quality assurance.
If you’re deciding how to organize your project, our guide to software development options explores the differences between building internally, outsourcing, and other development approaches.
Ghazenfer’s example brings the earlier mistakes together: even a capable team can spend time and money on the wrong solution if nobody identifies the underlying problem first.
Better Software Starts With Better Decisions
Software development mistakes often begin with decisions made before anyone writes code: assumptions about users, incomplete requirements, technology choices, or hiring the wrong expertise.
Before approving the next feature, development estimate, or hire, ask what problem the decision solves, what assumptions it depends on, and how you’ll know whether it worked.
Avoiding these mistakes won’t eliminate uncertainty, but it can help you protect your development budget and build software that’s easier to use, maintain, and improve.
