DEV Community: Nico Hartmann

Dating the Crawler

Nico Hartmann — Thu, 21 May 2026 20:31:10 +0000

There is this one moment after you have written the last line of code, optimized the last stylesheet, and finally uploaded the website to the server. You lean back, sip your coffee, and feel that childlike urge to type your own name into Google. Not because you don't know who you are, but because you are looking for validation. In my case, the result was sobering. Nico Hartmann is not a rare name. There are Nico Hartmanns who play football, Nico Hartmanns who are active in local politics, and probably hundreds of Nico Hartmanns who simply exist without bothering the internet with their presence. But there I stood, somewhere on page five or six, buried under an avalanche of namesakes. In that moment it became clear to me that I had not just built a website, but a digital monument standing in the deepest forest where nobody sees it. The need to climb up the rankings was suddenly no longer just a logical next step, but a matter of honour.

SEO is the magic word that gets hammered into you in every marketing blog. Search Engine Optimization. It sounds like an exact science, almost like alchemy, but in reality it is the only measure with which I can manipulate Google and the like. You try to outsmart a system that is smarter than yourself by feeding it exactly what it wants to hear. So I started equipping every single subpage with correct titles and descriptions. Every meta tag was polished, every headline was reconsidered three times. You feel a little like a fraudster trying to sneak into an exclusive party. The goal is clear: the search engines must like it. It is no longer about what the human reader thinks, but about what the algorithm spits out in its dark data centres.

The Capitulation of Language Before Statistics

The whole thing has a frightening similarity to LinkedIn. We all know this platform where people pat each other on the back and inflate their CVs until they almost burst. SEO is basically nothing other than digitally stroking one's own ego. The only difference is the target audience. Instead of recruiters or potential business partners, I want to impress robots. I write texts for beings without consciousness that count words, calculate keyword densities, and measure loading times in milliseconds. It is a bizarre form of modern communication in which the human being only plays the role of the supplier, while the bot decides whether you are relevant or not. When the bot smiles, the ranking rises. When the bot frowns, you remain buried in digital insignificance.

In theory, SEO sounds quite simple. You take a few keywords, build them into the text, and wait for the world to discover you. But reality catches up with you faster than you can spell keyword research. It gets damn quickly very complex. This is mainly because different search engines have different requirements. What Google loves, Bing might ignore, and DuckDuckGo has its own rules anyway. Moreover, you have to accept that you cannot be found for everything. You cannot be the king of the internet if you have no army. So you have to find an appropriate niche. For me that was quickly clear: IT lecturer and software development. Those are the terms with which I earn my bread and under which I want to be found.

However, this is where the strategic dilemma begins. I am also a trainer, and I would actually have loved to include that word in the title as well. It describes part of my identity and my daily work. But the hard reality of search engine optimization says no. If I were to throw even more keywords into the ring, I would dilute my focus. Every additional word is a potential disruptive factor that diminishes the relevance of the main terms. It is a constant balancing act between what you actually want to say and what the search engine still considers focused enough. SEO forces you into reduction. You mutilate your own description just to not appear too complex in the eyes of an algorithm. It is the capitulation of language before statistics.

The Curse of Internationality

As if that were not already enough work, the problem of multilingualism came along on top of everything else. I made a conscious decision in favour of multilingualism in German and English. The thought behind it was simple and perhaps a little naive: I simply wanted to be able to repost my blog entries on English-language sites as well. Internationality also always sounds good in a portfolio. My plan was to generate backlinks with this, which in turn would push my search ranking upward. A backlink from a reputable English site is like a gold medal for your own domain. So far, so logical. But the implementation transformed my clean website concept into a bureaucratic monster made of links and language tags.

The surprise came when after some time I actually searched for Nico Hartmann IT lecturer. A small triumph germinated within me when I actually saw my name in first place. But the joy lasted only seconds. Google did indeed present me at the very top, but the description was in English. There you sit in Germany, searching for a German term, and you get served an English snippet. That is the moment when you would love to throw the keyboard out of the window. Google had understood that I am important, but not which language is appropriate for this specific context. The algorithm rolled the dice and I lost.

So it was: back to the drawing board. I had to set hreflang attributes. For the layperson this sounds like technical triviality, for the website operator it is the attempt to draw the search engine a map that it should please not ignore. You explicitly tell Google which page is intended for which region and which language. And then the great waiting begins. SEO is not a sprint, it is a marathon through mud. You wait one to two weeks until the merciful crawlers from Google finally deign to look at the website anew. You feel like a supplicant before the throne of a capricious king, hoping that your corrections will this time be graciously received.

This entire process is a lesson in humility and frustration. You invest hours in optimization, only to discover that you are dependent on the whims of a corporation that changes its algorithms faster than you can adjust your own description. It is a permanent fight against windmills, where the windmills consist of server farms and the lance is a text editor. You are not optimizing for the user, you are optimizing for the machine, in the hope that in the end a human being will still find their way to the page. It is an absurd theatre in which we all play our roles, just to grab a small piece of visibility in an ocean of information.

And while I sit here waiting for the next crawl, I ask myself whether all of this is really worth the effort. The answer is a frustrated yes, because in today's world you do not exist if you are not on the first page. You submit to the dictate of the search engine, adapt your language, cross out words that you actually like, and set cryptic attributes in the header. All for that one moment when the search for your own name delivers exactly the result you have so laboriously purchased. It is a digital ego trip that costs you more nerves than any software development, but in the end vanity wins over reason.

The Anatomy of Keywords

When you dive deeper into this swamp, you quickly notice that keywords are like small pets. You have to care for them, feed them, and assign them exactly the right place. Choose the wrong ones and they bark at you or run away. In my case, the decision for IT lecturer and software development was a purely strategic choice. I could also have taken IT teacher or code coach, but who searches for those? You spend hours with tools that tell you how often a term is searched for, only to then discover that the competition for these terms is so gigantic that you as a lone fighter barely have a chance. So you search for the gap, for the golden middle ground between relevance and feasibility.

It is this constant balancing act between the ego and the algorithm. You might want to call yourself a "visionary for digital transformation," but that is of little use if the market is simply demanding a "Python course." This discrepancy forces one to break down their own identity into bite-sized morsels that can be easily digested by search engines.

In this context, keyword research is often less of an exact science and more of a psychological poker game against user intent. You analyze long-tail keywords and niche terms in the hope that the specific combination of expertise and location hits exactly the right nerve for those who won't just click on the first mass-market offer they see. At the end of the day, the realization remains that visibility is not created by the loudest terms, but by the cleverest positioning in the shadow of giants.

The Curse of the Technology Behind the Language

The decision for multilingualism was, looking back, like the attempt to fly two aeroplanes simultaneously. You think you simply write everything twice and that is that. But Google sees it differently. For a search engine, duplicate content is a red flag. If you are unlucky, the algorithm penalizes you for trying to dance at two weddings at once. The solution is precisely those hreflang attributes I have already mentioned. These small code snippets are the diplomatic representatives of my website. They tell Google: Hey, this here is the German version for the Germans and that there is the English version for the rest of the world. Please do not throw them into one pot.

It is fascinating and alarming in equal measure how much time one spends on technical overhead that has absolutely nothing to do with the actual content. I want to write about software development, about didactics in IT, about modern technologies. Instead I spend my evenings validating XML sitemaps and checking whether my canonical tags are correctly set. You become the bureaucrat of your own creativity. Every new page, every new blog post drags a long tail of administrative tasks behind it. If you do not do this, the contribution remains a lone voice crying in the wilderness. You no longer write for the joy of writing, you write for the indexing.

The Arrogance of the Crawlers

There is hardly anything more frustrating than the waiting time for Google's bots. These digital insects crawl through the net, index billions of pages, and decide over success or failure. You have no influence over when they come. You can invite them via the Search Console, essentially hold the door open for them and roll out a red carpet, but in the end they come when they want. This uncertainty is poison for anyone who wants to see fast results. You change a small thing that you are convinced will bring the breakthrough, and then you stare at an unchanged search bar for days.

During this time you begin to doubt yourself. Was the hreflang attribute really correct? Have I perhaps forgotten a quotation mark? Why is the English description still being displayed even though I have prioritized the German page? It is a psychological game. Google is the invisible referee who changes the rules during the game and never tells you exactly what you have done wrong. You receive only vague hints and have to figure out the rest through trial and error. It is a form of digital servitude into which we have voluntarily entered because we need visibility like the air we breathe.

I stand here with a website that is technically speaking flawless, but which is still fighting against the shadows of my namesakes. I have learned that IT lecturer is my anchor and that I must enjoy the English language with caution if I want to dominate the German market. It is a laborious path, characterized by technical trivialities and the constant concern for the goodwill of an algorithm. But ambition has been awakened. If Google wants to see me as an Englishman, I will prove to Google that I am the German IT expert it is looking for. The battle for Nico Hartmann has only just begun.

The Tyranny of Backlinks or Why Quality Alone Is Never Enough

After I had more or less navigated around the technical hurdles of multilingualism and metadata, I ran into the next great monster in the SEO ocean: authority. It is simply not enough for Google that I claim to be a competent IT lecturer. The search engine wants to see proof. In the digital age, this proof takes the form of backlinks. A backlink is basically a recommendation from another website. If a reputable IT site links to me, the Google algorithm thinks to itself that this Nico Hartmann is probably not a charlatan after all. So I began refining my strategy for reposting my blog entries on English-language platforms like Medium or Dev.to. The goal was clear: I wanted to use the reach of these giants to redirect a little of their digital shine onto my own small domain.

It is a strange form of digital prostitution. You write high-quality content, give it away practically for free to large platforms, and hope in return for a small, clickable link that leads the crawler back home. But here too complexity lurks. There are no-follow and do-follow links. The former are as useful for rankings as an alcohol-free beer at a hacker party, the latter are the digital gold. Of course, most large sites give out only the inferior links by default, in order not to dilute their own ranking. So you fight at the front line for recognition and are often thrown only crumbs. Nevertheless, this process is without alternative if you do not want to stand forever in the shadow of the other Nico Hartmanns of this world.

The Dilemma of Content Recycling

The reposting on English sites brought me to yet another painful realization. You cannot simply copy the same text one-to-one. Search engines are allergic to laziness. Whoever simply copies will be ignored. So I had to rewrite my own texts for the English platforms, adapt them, and give them a new spin. The whole thing was supposed to serve to underscore my expertise as a software developer, but in the end I spent more time rephrasing sentences than on actual programming. It is a paradoxical vicious circle: in order to be perceived as an expert in software development, you have to stop developing software and start becoming a full-time copywriter for yourself.

Particularly insidious is the psychological component. You observe the statistics. You see how many people have read the English article, and hope that at least a fraction of them will find their way to the original portfolio page. But most users remain in their ecosystem. They read on Medium, perhaps clap briefly, and move on. The search engine does register the connection, but the hoped-for massive rise in rankings often remains a quiet background noise. You feed the beast with ever more content, in the hope that it will be satisfied at some point and grant you your place in the sun. But the beast Google never clocks off.

The Waiting Time and the Grace of the Crawlers

When you have then scattered all backlinks and checked all hreflang attributes for the tenth time, the phase of absolute powerlessness begins. You can do nothing more but wait. The internet is a vast memory that unfortunately forgets very slowly and learns even more slowly. You check the Search Console daily. You look at the impressions, the clicks, the average position. It is like watching grass grow, except that the grass sometimes decides in the middle of the night to retreat back into the ground.

Once I suddenly appeared in first place for a completely irrelevant search term, simply because I had mentioned it once in a subordinate clause. That is the irony of SEO. You optimize like someone obsessed for IT lecturer and software development, and Google decides instead to rank you for a typo in a code example. You feel not understood by the artificial intelligence, but rather mocked. The crawlers are like civil servants in a dusty authority: they work according to rules that were established years ago, and have no interest in your personal urgency. If they decide that your English description is more important than your German one, then that is how it stays for now, until the file lands back on top of the pile a few weeks later.

The Niche as a Lifeline

In this chaos, concentration on the niche is the only way to not go mad. I have come to terms with the fact that I will never stand in first place for the word software development alone. Corporations with million-dollar budgets and whole armies of SEO specialists are fighting there. But for Nico Hartmann IT lecturer? That is my playing field. Here I can win if I remain persistent. The restriction here is not a weakness, but a necessary survival strategy. It is better to be the king of a small village than a beggar in a metropolis.

Nevertheless, this bitter aftertaste remains: that you are optimizing your digital presence not for people, but for a mathematical formula. Every time I leave out the word trainer just to not jeopardize the keyword density, it feels like a small betrayal of my actual work. We build websites for machines that pretend to decide for people. It is a simulation of relevance. When I write a text today, I no longer ask myself first whether it is useful for my students, but whether it offers enough semantic connections to satisfy Google's semantic search. We adapt our thinking to the structure of the search engine.

The Outlook into Madness

What remains at the end of this rant? SEO is a necessary evil, a modern form of indulgence trading. We pay not with money, but with time, nerves, and our linguistic integrity. I will continue to set hreflang tags, hunt backlinks, and polish my metadata. Not because it is fun, but because the alternative is digital invisibility. And in an industry where online presence is the new business card, you simply cannot afford to be invisible.

Perhaps Google will come to its senses in a few weeks. Perhaps the crawler will recognize that the German page is actually the better choice for German search queries. Until then I will continue to cast hateful glances at my monitor when the English description appears at the very top again. SEO is a fight you never win entirely, you can only keep fighting it until you either end up on top or lose the inclination. And since I am a stubborn IT lecturer, I will probably keep going until Google finally spells my name the way I want it.

SEO is the art of dressing up for robots so that people can find you.
Multilingualism is a technical nightmare that has a preference for delivering the wrong search results.
Backlinks are the currency of the internet, but the exchange rate is merciless.
Your own identity must yield to the niche if you want to survive in the rankings.

Sometimes I ask myself whether the other Nico Hartmanns out there are fighting the same battle. Whether the footballer is also frustrated because my blog post about software development appears above his latest match report. If so, that is at least a small consolation. In the arena of search results there are no friends, only competitors for the attention of an algorithm that knows no mercy. At the end of the day I sit again in front of the computer, adjust the next description, and hope for the best. Because whoever does not optimize does not exist. And I would quite like to exist, at least on page one.

The Illusion of Replaceability

Nico Hartmann — Wed, 06 May 2026 08:10:20 +0000

The panic in the tech industry is palpable. In forums, social networks and office kitchens, the same question keeps coming up: will artificial intelligence destroy the profession of software developer? Anyone reading the headlines from the major tech giants might believe we are only months away from a world where a simple text input creates complex software systems. But those familiar with the history of computer science will recognize a familiar pattern in this euphoria. The attempt to eliminate the developer as an intermediary between problem and solution is almost as old as the computer itself.

An old promise, repackaged

Even in the 1950s and 60s, there was the promise that programming would soon be accessible to everyone. COBOL was developed with the intention of being a language so close to the English business language that managers could write their own logic. The abstraction from binary code and assembler to readable sentences was thought to render the experts obsolete. The result is well known: COBOL became one of the most complex and maintenance-intensive languages in the world, still requiring highly specialized experts.

Later came SQL with the promise that end users could simply formulate their own database queries. Again, it turned out that syntax was not the problem, but the structural logic behind it. More recently, we saw the rise of low-code and no-code platforms. They have all found their place, but they have not replaced the software developer. On the contrary: they have merely shifted the bar for what we consider standard.

What a developer actually does

To understand why AI falls into this category of tools and does not herald the end of the craft, we need to look at what a developer actually does. It is often mistakenly assumed that a programmer's main task is typing code. But that is only the final implementation. A developer takes tools, techniques and deep-seated skills and deploys them purposefully to produce an output: the program. That program is in turn only a means to an end, to achieve a real-world outcome. Whether optimizing a supply chain, securing a transaction, or providing a communications platform.

This process requires something we laboriously learn over years: algorithmic thinking. It is about translating vague human wishes into strict, error-resistant logic. We learn to anticipate edge cases, plan for scalability, and weigh the long-term consequences of an architectural decision.

AI models, especially Large Language Models (LLMs), merely simulate this process. They place a powerful output generator in the hands of every non-developer. The problem is that someone without a solid grasp of the subject matter can now produce things whose quality they cannot assess. The result is a flood of code fragments that appear to work at first glance, but collapse under the slightest load or requirement for maintainability. The outcome is either completely unusable or so poor in quality that the damage outweighs the benefit.

LLMs: Pattern recognition, not intelligence

We must be clear about what LLMs are at their core: they are phenomenal pattern recognition machines. They have seen billions of lines of code and have learned which sequence of characters statistically tends to follow another. Everything else we perceive as intelligence is more of a side effect of these statistical probabilities.

These models possess no capabilities anchored in the physical or social reality of our world. Creating a software product means generating real value. That requires an understanding of the context in which the software operates. An AI cannot question the true intention of a client. When a customer says they want feature X, an experienced developer often recognizes that the actual problem is Y and that feature X would only make things worse. The AI simply delivers feature X, without sense or understanding of the business consequences.

Even luminaries in this field express massive skepticism. Yann LeCun, Turing Award winner and one of the pioneers of modern AI, describes the current LLMs as a technological dead end on the path to genuine intelligence. He argues that they lack an understanding of the physical world and causal relationships. His proposed solution is a so-called world model, an AI that learns through observation and interaction, like a human. Whether such a model is technically feasible at all or remains a theoretical wish remains to be seen in the distant future.

The spectacle on the world stage

Meanwhile, we observe a bizarre spectacle on the world stage. The wealthiest people and most powerful corporations are racing to be first to announce superintelligence. It is about market power, stock prices, and ego. We can only hope that this digital arms race does not set the global economy ablaze while the foundations of our digital infrastructure are destabilized by a flood of AI-generated mediocrity.

AI is in its current state a tool. A powerful one, yes, but still just a tool. And like every instrument in human history, it is only as good as the hand that wields it. A hammer does not make a layman into a carpenter, and an LLM does not make a layman into a software architect.

The real danger: the labor market

The real danger, however, lurks from an entirely different direction: the labor market. The current perception of AI is causing dangerous uncertainty. Many companies are hesitating to hire, and young people are shying away from beginning a career in software development, fearing they will soon be unemployed. At the same time, experienced developers currently struggling to find jobs are reorienting themselves toward other industries.

If in five to ten years we reach the point where the baby boomer generation of senior developers retires, we will face an immense surge in demand. But there will be no candidates on the applicant side, because the training pipeline has been interrupted. We are heading toward a massive skills shortage that is being triggered precisely by the unfounded fear of one's own replaceability. The software of the future will be more complex than ever, and we will need every sharp mind to tame it, with or without AI as an assistant.

Form vs. content: a fundamental error in thinking

In the debate about artificial intelligence, a crucial mistake is often made: we confuse form with content. Because a computer program is now capable of writing syntactically correct code, we conclude that it also understands the problems that code is meant to solve. But software development is primarily a discipline of problem-solving and only secondarily one of writing. Those who believe that LLMs will replace the developer's profession reduce the entire field to pure syntax production. In doing so, however, they fundamentally misunderstand the nature of what we call digital value.

When we ask an AI to write an authentication function, it draws on thousands of examples it has seen during training. It does not "know" what security means. It does not know what a hacker is or what the legal consequences of a data breach are. It merely replicates the pattern of a solution that was used in the past for similar tasks. This works excellently for standard problems, but leads to catastrophic results when it comes to innovation or highly specific edge conditions.

Abstraction and knowledge transfer

A key aspect of the human developer is the ability for abstraction and the transfer of knowledge from completely unrelated fields. A good software architect uses analogies from logistics, biology, or even sociology to design systems that are resilient.

AI, by contrast, is trapped within its training dataset. It cannot reinvent the wheel; it can only redraw it in countless variations. In a world that is developing technologically as fast as ours, however, clinging to past patterns is often a recipe for technical debt. We need developers who are able to question existing paradigms and chart entirely new paths, rather than merely generating the most probable continuation of the past.

Responsibility and causality

Another critical point is responsibility. Software today controls hospitals, power grids, braking systems, and financial markets. A program is a legally and morally binding set of rules. When an AI generates code that fails at a critical moment, who bears responsibility? The model provider categorically disclaims this in their terms of service. The user, who has no idea about the code, cannot accept responsibility, because they could not have recognized the danger in the first place.

This is where the indispensability of the expert becomes clear. A developer stands behind the correctness of their work with their expertise and professional ethics. They validate, they test, and they understand the causal chains behind every line. An AI model knows no causality, only correlation.

Economic interests behind the hype

One must ask why the promises of the AI evangelists are proclaimed so loudly. This is less about technological truth than about economic interests. For companies, the idea of replacing expensive and often headstrong experts with cheap computing time is tempting. But this calculation is short-sighted. What is saved in labor costs is paid back double and triple later in fixing errors arising from flawed system design. History is full of companies that tried to rationalize away their IT departments, only to find they had amputated their most important organ of innovation.

The claim that we are on the verge of a superintelligence that will eclipse all human cognitive abilities often serves merely to funnel investor money into coffers. The reality is more sobering. We are dealing with highly specialized tools that can relieve us of monotonous tasks. They can write boilerplate code, summarize documentation, or find simple bugs in small scripts. That is an enormous gain in productivity. But it is not a replacement for the human who sets the direction.

The developer of the future will spend less time typing standard code and more time designing systems, analyzing requirements, and overseeing AI tools.

The psychological component

We must also talk about the psychological component. The current mood in the labor market is causing paralysis. When we suggest to young talents that their chosen profession has no future, we destroy the foundation for the technological progress of the coming decades.

Software development will change, as it always has. In the past, we had to worry about memory management at the bit level; today we work in cloud environments with enormous abstraction layers. AI is just another layer. It requires new skills, perhaps the ability to give more precise instructions or to audit AI-generated code more quickly, but it still requires the human mind.

The demographic time bomb

When we look at demographic trends, the scale of the coming crisis becomes clear. Over the next ten years, a significant portion of the most experienced developers will leave the labor market. If by then the next generation has been deterred by false narratives, we will be faced with a digital pile of rubble.

Companies will be desperately searching for people who understand how the complex systems under the hood work, systems that were only superficially attended to by AI. We will experience a renaissance of craftsmanship in computer science, where those who truly master the fundamentals will be more valuable than ever.

Conclusion

In conclusion: AI is not a replacement for the developer, but a challenge to their professionalism. We must not be blinded by the glittering promises of the billionaires who want to sell their own products as godlike beings. We must return to objectivity.

Software development is an engineering art based on experience, intuition, and a deep understanding of the world. As long as an AI feels no pain when a system crashes, and no joy when a problem is elegantly solved, it will never be able to grasp the soul of a solution.

The path to genuine intelligence is long, and perhaps it cannot be reached through pure mathematics and statistics at all. Until then, we remain the architects of the digital world and AI is merely our new, somewhat wayward assistant.