Search engines are evolving, and searching for information is becoming more intuitive and efficient every year. But there’s a downside: the question of how search engines work is also becoming more complex every year. And when you work in SEO, you have to search for answers every day.
What we know for sure: understanding how Google algorithms work depends heavily on who’s talking about them. Several categories of experts regularly discuss them:
- official Google representatives;
- engineers from these same companies;
- my fellow SEO specialists;
- those who study actual search behavior (also SEO specialists).
Let’s look at what all these people are saying and which of them can be trusted.
Point of view #1. Official representatives of search engines
Imagine a search engine as a highly attentive librarian who knows the contents of millions of books. When you ask a question, it instantly finds the most relevant answers. That’s roughly how Google employees explain how their algorithms work.
According to them, the search begins with “spiders”—special programs that constantly navigate the internet, following links and memorizing website content. They peer at each page, as if examining it through a magnifying glass, and store the information in a gigantic database called an index.
When you enter a query, the system doesn’t search the entire internet in real time. Instead, it checks the index, like browsing a library catalog. Algorithms analyze millions of factors to select the most useful pages. The main criteria are relevance to your query and content quality.
Search engine employees always emphasize that systems don’t simply look for keywords. They try to understand the meaning of the question. For example, if you type “why is the sky blue” into the search bar, the algorithm will find a scientific explanation, not pages that simply repeat these words.
User satisfaction is paramount for search engines. Therefore, they monitor how people interact with results: if many quickly return to the search, it means the page hasn’t answered the question, and its ranking will drop. Systems also value sites with a user-friendly design, fast loading times, and reliable information.
How I know this: here you can find an analysis of some quotes from Google executives.
Viewpoint #2: Google Engineers
For search engine creators, their brainchild is not just a program, but an intelligent assistant. It must understand people almost like a human conversational partner. Engineers dream of a search engine capable of reading between the lines and anticipating user needs. The main goal of ideal search, according to developers, is not simply finding words from a query, but understanding their true meaning.
For example, when a person asks “how to make a pie,” the system must consider several factors. Perhaps they’re a beginner and need a simple recipe? Or are they allergic to certain foods? Or are they looking for a no-oven option? This type of search requires true artificial intelligence capable of contextual analysis.
Engineers are striving for a system that works like the ideal librarian: it doesn’t simply provide books on request, but can also recommend items the reader never even considered. For example, if you search for “best resorts,” it will suggest options tailored to your needs, taking into account your budget, preferences, and previous trips. Search engine developers are looking to the future and imagining what search will be like in a few years. It won’t just be a search bar, but a truly intelligent assistant.
Currently, search operates according to specific rules defined by programmers. But soon, everything will change—artificial intelligence will learn to understand what we need. It will be able to grasp the meaning, not just search for words in a query. For example, if you type “what to read to a 5-year-old,” the system will understand that you need not just books, but age-appropriate fairy tales with pictures.
Today’s search distinguishes between text, images, and video. In the future, the system will search everything at once and understand the connections between different formats. Ask about the Eiffel Tower and you’ll get not only articles, but also a selection of the best photos, videos from different angles, and even audio guides.
The most exciting thing is that search will anticipate our questions. The system will offer help even before we ask. For example, if you frequently search for recipes, it might automatically show you breakfast suggestions in the morning. And if the answer isn’t clear, you can simply ask again, just like you would with a human.
This future is just around the corner. Soon, search will no longer be a tool, but a true digital assistant that truly understands us at a glance.
The most important principle for developers is absolute objectivity. In their ideal world, search results should not be dependent on commercial agreements or personal preferences. Only facts, only relevance, only benefit to the user.
But most importantly, engineers want to create a search that learns along with humanity. One that can explain the theory of relativity to a schoolchild today, help a scientist make a discovery tomorrow, and suggest a solution to a common problem the day after. A search that becomes smarter, kinder, and more useful every day.
How do I know this: here’s one analysis of engineers’ quotes
Point of View #3: SEO Specialists
SEO specialists view search engines as a complex puzzle to be solved. They know Google’s official rules, but they also look for hidden patterns that help websites rank at the top of search results.
Many SEO experts view the search engine as a strict teacher, rating websites based on hundreds of different criteria. They try to guess which factors are most important: perhaps the number of links to a site, or page load speed, or the time users spend viewing content. At the same time, they understand that evaluation rules are constantly changing, and what worked yesterday may not work tomorrow.
SEO-специалисты часто сравнивают свою работу с садоводством. Они «выращивают» позиции сайта, заботясь о множестве деталей: «удобряют» контент ключевыми словами, «поливают» его внутренними ссылками, «подрезают» технические недочеты. При этом они знают, что даже самый ухоженный «сад» может не дать урожая, если алгоритмы поисковиков решат изменить правила.
Many in the SEO community believe that search engines are not simply neutral technical tools, but complex ecosystems with their own interests. They notice that commercial queries often favor large companies over the most useful websites, and they try to find ways to “negotiate” with the algorithm.
The key characteristic of an SEO specialist’s mindset is constant experimentation. They try different approaches, analyze the results, and draw conclusions, creating their own map of the underlying dynamics in search results. At the same time, they understand that it’s impossible to completely decipher the algorithm—only to find the patterns that work.
Get StartedViewpoint #4: How Search Engines Actually Work
Reality, as usual, is a compromise between what companies themselves say, technical capabilities, and market conditions. Here are the patterns that search engine researchers are noticing:
- Search engines do strive for relevance, but their algorithms aren’t perfect—sometimes sites with aggressive SEO climb to the top.
- AI plays a huge role, but it doesn’t completely replace manual filters and moderation (for example, penalties for spam).
- SEO optimization works, but the rules are constantly changing—what worked yesterday may lead to penalties tomorrow.
- Commercial factors influence search—large brands and paid partners sometimes gain an advantage even if their content isn’t the best.
So whose truth is closer to reality?
It’s safe to say that Google are telling the truth, but not the whole truth.
Engineers envision an ideal system, but in practice, compromises are forced. SEO specialists are often right about tactics but wrong about long-term trends. Real search is a mixture of algorithms, manual edits, and market forces.
The main conclusion is this: SEO isn’t just following rules, but constant adaptation. The best strategy is to create high-quality content while also testing hypotheses and monitoring algorithm changes.
