Today, I want to discuss a phenomenon that I noticed at the beginning of my development journey. I’ve long wanted to share these thoughts and get feedback from more experienced developers. I’m confident that this approach is useful not only for beginners but also for experienced specialists — especially when they’re exploring a new direction, such as a different programming language or framework, although its effectiveness noticeably decreases with growing experience.

In today’s development world, beginning programmers constantly hear advice like: “Google the solution, surely someone has already encountered this!” or “Ask ChatGPT, it will help faster than you figuring it out yourself.”

The search for ready-made answers has become so natural that independent problem analysis seems like a waste of time to many. We live in an era where programming is increasingly turning into matching existing solutions rather than creating new ones. But what if we look at this differently? What if instead of immediately turning to search engines or AI, we trust our intuition and basic knowledge to truly understand the technology?

Of course, many developers use the “copy and paste” approach, and there’s nothing wrong with that. Under strict deadlines and constantly growing volumes of information, it often seems like the only effective solution. But it’s important to remember: true mastery lies in finding the balance between using ready-made solutions and developing your own thinking.

Today, I want to talk about an approach that I accidentally discovered when I was just starting my development journey — Naive Problem Solving. This method not only changed my attitude towards learning programming but also helped me understand the technologies I worked with more deeply, as well as find non-standard and sometimes more elegant solutions to complex problems.

How It All Started

When I began diving into frontend development, at university (I study at HSE University in the Design and Programming track) this direction received only partial attention, and development wasn’t covered deeply enough. I lacked practice and understanding of details, so I decided to study frontend independently. Instead of trying to cover everything at once, I focused on basic principles and key concepts, deliberately avoiding diving into complex details in the early stages. I thought this approach would allow me to move to practice faster and not drown in a sea of theory. But the real discovery happened when I encountered my first serious problem.

Instead of the usual search for a ready solution on the internet, I decided to figure it out myself. Relying only on basic knowledge and logic, I investigated the problem step by step, analyzing code and testing different options. This process seemed unusual and complex but brought unexpected results. Like many beginners, I first thought about taking the beaten path — searching for answers on forums. But something pushed me to try to cope on my own, using only existing knowledge and logical thinking.

Initially, this approach seemed ineffective. At times, I felt like I was going in circles, trying to reinvent the wheel. But gradually, I started noticing something amazing: by solving problems independently, I wasn’t just developing technical skills, but I was beginning to think differently. With each solved problem, I understood more deeply how the technologies I worked with functioned. And sometimes my “naive” solutions, in my opinion, turned out to be even more practical and elegant than conventional approaches.

What is Naive Problem Solving?

When I began to comprehend my approach, it seemed like something unique, something I had formulated for myself. I saw potential in it: it not only develops thinking but also helps find non-standard solutions. However, later I learned that this method has long existed and is actively used in educational practice. It’s especially common in programming education, where students are given the opportunity to try solving complex problems independently before explaining traditional methods. And although I came to it intuitively, this only confirms its effectiveness.

Naive Problem Solving is a method where a developer intentionally limits themselves in using ready-made solutions. Instead of immediately seeking others’ experience, they explore the problem from scratch, relying only on their knowledge, intuition, and logic. It’s somewhat similar to how a child solves a puzzle: they don’t have pre-learned methods, they just experiment until they find the right path.

At first glance, this approach might seem inefficient. After all, why waste time if you can just find the answer? But in practice, Naive Problem Solving helps develop a deep understanding of technologies. When you look for a solution independently, you start noticing connections that usually remain outside your field of vision. Gradually, you’re not just solving problems — you’re learning to think differently, analyze problems from various angles, anticipate possible difficulties, and find ways to solve them.

This method doesn’t always give quick results, but it forms thinking that’s impossible to develop by just copying solutions from the internet or relying on neural network responses. It also helps find fresh, non-standard solutions that might turn out to be even more effective than conventional ones.

Why Does It Work?

When you solve a problem independently, you’re forced to analyze it from different angles, trying to understand the details and possible solution variants. This develops the ability for systematic thinking and teaches you to view the problem not as a set of separate fragments, but as a unified construction where all elements are interconnected.

Another important effect of this approach is a deep understanding of technology. When you’re not just copying someone else’s solution but immersing yourself in the process logic, you inevitably encounter nuances that might otherwise remain outside your attention. Over time, this leads to technologies no longer seeming like a black box: you don’t just apply them, but understand how and why they work.

But perhaps the most valuable aspect of Naive Problem Solving is the possibility to find truly innovative solutions. By not following templates and not limiting yourself to others’ approaches, you look at the task with fresh eyes. Sometimes it’s exactly this process, when you first try “naive” paths and then analyze them, that leads to unexpected and more convenient or effective results than classical solutions.

An Example from My Practice

This approach first struck me while working on a React client application task. I needed to create a multi-page website without server-side generation, with good search engine indexing being an important requirement. It was a shortcuts catalog, and its SEO optimization directly affected search convenience and user attraction.

At that time, I didn’t know about existing solutions to this problem, but I understood that standard client-side rendering on pure React makes content indexing difficult for search engines. The problem was that search engines don’t always correctly process dynamically loaded content, and since the project required a serverless approach, I needed to find an alternative solution. I decided to approach the task from scratch: if search engines poorly perceive JavaScript-generated content, why not form HTML in advance?

This led to the idea of writing a small Python script that automatically generated static HTML pages from catalog data, including pre-formed content versions for indexing. After page loading, the static HTML remained available for search engines, and immediately after React initialization in the browser, it was replaced with interactive components, ensuring dynamic content updates. This allowed search engines to index content without problems, and me to create a solution that didn’t require complex server infrastructure.

Later, I learned that this approach essentially repeats the concept of Static Site Generation (SSG), and also has similarities with Islands Architecture — a model where most of the page is rendered statically, and interactive elements are connected in necessary places as dynamic “islands.” I didn’t know about this architecture then, but intuitively came to a similar solution.

I plan to talk about this case in more detail in one of my next articles, where I’ll analyze how I used Python to improve SEO for a multi-page React site, what technical solutions I applied, what difficulties I encountered, and what results it gave.

This case showed me that sometimes “naive” problem investigation leads to simpler and more effective solutions that might otherwise remain outside the field of vision.

Balance Between Learning and Practice

Naive Problem Solving isn’t an alternative to studying standard solutions, but a complement to it. I’m not advocating completely ignoring others’ experience or refusing to search for information. It’s important to understand that solving problems independently isn’t a way to “isolate” yourself from existing knowledge, but an opportunity to look at the problem from a different angle, even with complete or partial absence of context about possible ways to solve it.

For myself, I developed an approach that helps me find balance. First, I try to solve the problem independently, using only my knowledge and logic. Then I study existing methods to understand how it’s solved in the industry. After this, I compare the found solutions with mine, analyze their pros and cons, and look for what can be improved.

This process helps me not only understand technologies more deeply but also develop creative thinking. Sometimes my solutions turn out to be more suitable for specific cases than standard methods. And sometimes I realize I made a mistake, but even this becomes valuable experience. After all, it’s important not just to find the answer, but to understand why it works.

I also noticed that independent problem-solving becomes even more useful if you record your actions. Documentation helps better understand the process and gives the opportunity to return to it later. Discussing your findings with colleagues or publishing your experience is another way to deepen understanding. Often, feedback helps see what can be improved or find a new approach that wasn’t considered before.

The balance between independent solution searching and studying existing practices is important not only for learning but also for forming engineering thinking. It’s not just a way to work more effectively, but an opportunity to learn to see technologies more deeply.

This approach doesn’t just help learning, but forms a new perception of problems and ways to solve them. It develops creativity, makes you delve deeper into technologies, and search for non-standard paths. For beginners, it’s a chance to feel like real engineers creating solutions from scratch, and for the industry — a source of fresh ideas and alternative approaches and solutions.

I’m interested to know what you think about this method. Perhaps you’ve had similar experience, or conversely, you think this approach is ineffective? Share your thoughts in the comments — I’ll be happy to discuss this topic.