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I want to put my thoughts "on paper," mainly to get other perspectives on something I've been thinking about a lot. I'm especially interested in hearing from people who, like me, feel that a different life pattern is emerging. I call it AI Native. Why do I think I have any right to talk about this? It's not because I've been using OpenAI products for about 3 years and I'm in the top 1% of active users. Not because I have 5 paid subscriptions to different models and I understand well what I'm paying for. Not because 70%+ of my communication with LLMs happens through voice, or because we use various LLM combinations and "councils" at work, plus locally deployed SLMs on our computers and other stuff. Not because a significant part of my work involves various models. No. It's more about how clearly I see the value of the augmented intelligence concept. And I consume content across a very wide spectrum of opinions, from founders of companies building foundational models and mathematicians configuring the mathematical paradigms behind these products, to philosophers calling for slowing down (but not stopping) the development of these technologies.
LLMs have already become part of everyday life, even if there's still a lot of noise and info-marketing around them. The hype continues, courses, info-marketers and "implement in 7 days" offers keep multiplying, but the numbers show a picture of growing market maturity. To understand the scale: ChatGPT now has 600-900 million monthly users and 65-68% market share. The share is slowly declining, but absolute numbers keep growing. Google's Gemini is already at 450-650 million users, 18-20% share, and that's the fastest growth, basically doubling in a year thanks to deep integration with Search, Gmail and Docs. Grok from xAI is smaller so far, 30-60 million users and about 3%, but growing through native integration with X. Claude from Anthropic stays in the 15-30 million range, 2-3%, with a strong concentration of developers and knowledge workers. The analogy from other industries is simple: just like nobody "implemented" a browser or a messenger, soon nobody will "implement LLMs" either. They'll become the basic interface layer between humans and any digital action. This is already mass market, quickly approaching internet penetration numbers overall. This isn't the future, it's a rapidly changing present. Of course there are nuances: some people use it once a month to pick a phone, while for others a provider outage means work stops.
One recent conversation shows exactly how people use LLMs. A couple months ago I heard a respected thinker (in certain circles) argue that texts written with AI should be labeled. And at that moment it became clear how quickly even smart, educated people start falling behind the changes in the world. There could be many reasons: age, low technical literacy, humanities background. This particular thinker is from the social sciences, and the irony is that we're talking about society and behavior here, his direct area of expertise. The reality is that the line between "AI-generated text" and human-written text is rapidly disappearing. If I take two or three abstract ideas of my own, pass them to a model, and ask it to shape them into a clear, understandable message for a specific audience, is that AI or is it still me? At the consumer level, the spectrum is already almost maxed out: from counting calories and generating social media images to solving complex problems in school and work. We're effectively already living in an augmented intelligence model, where we connect an external intellectual layer to our own intellect every minute, passing it context and high-level tasks. This layer has limitations and quirks, but our "native" intellect has exactly the same problems: the need to rest and switch gears, a long list of cognitive biases, and a pretty innate capacity for hallucinations.
An LLM-native user isn't a developer or a prompt engineer, but someone who has models built into their thinking like the ability to reach for a calculator or a search bar. They understand that different models solve different tasks: one reasons better and holds long context, another writes code or text faster, a third is strong with images or data analysis. They know the value isn't in the model itself but in external tools: integrations, memory, context, data, APIs, conversation history. They comfortably use LLMs off-label: as a mirror for thinking, as a conversation partner for clarifying ideas, as a way to pull unformed thoughts out of their head and turn them into structure. They have intuition about usage practices, not in the form of manifestos but as internal boundaries where help ends and responsibility substitution begins. They know what models aren't good for: final decisions with high error costs, moral choices, situations where real empathy matters rather than simulated empathy. They feel how LLMs change thinking patterns, speed up the transition from idea to form, but can weaken the skill of sustained concentration.
And they already feel a kind of new ethics forming right now. For example, firing off a 145-page document with detailed deep research results from some model in response to a friend's question isn't exactly convenient for the other person. The person who asked you something doesn't expect to see you as just another LLM add-on. They need human intelligence that consciously expands its capabilities through LLMs, not one that delegates the right to think to them. A native LLM user understands that the volume of new content generation is now essentially unlimited, which means the other person probably doesn't have time to read a 145-page document, even a quality one. There's already a full-blown pattern where one person generates a message to another, and the other person, also using an LLM, analyzes the first person's message and responds in kind.
Against this backdrop, a lot of questions arise about the very near future: from deeply practical to philosophical. Here are just some of them.
Why do we need interfaces for endless e-commerce services and service providers? As a user, I have to scroll through pages of products matching my queries, but I have to, not because I want to. My OpenAI account, after 3 years of constant conversation with me, holds enormous context about me and can pick out exactly what I need for this particular situation. Will the classic interface of online stores and marketplaces stay the same, or will they turn into APIs for my personal account with one of the foundation models?
How do we make interaction with LLMs even more native? Tapping fingertips on plastic squares isn't what evolution designed us for. The augmented intelligence concept suggests we'll interact with our LLMs in ways much more natural for us.
Are there risks of declining cognitive abilities? On one hand, writing and calculators reduced the load on our brains for certain cognitive tasks, and we don't seem to have gotten dumber from it. On the other hand, one concept in neuroscience says that to keep our brains sharp, we need to regularly invest energy in figuring out unfamiliar problems. This process seems radically changed: from minor appliance repairs to picking a wine fridge and educational courses, LLMs now take on a significant part of the work. There's early research on this, but looking at the design of these studies, particularly fMRI activation of different brain regions in people who actively use LLMs versus those who don't, I wouldn't trust them yet and would wait for something more substantial. So this question remains open for now.
A separate big topic is the restructuring of many industries and sectors, and it's a restructuring much more complex and interesting than the primitive concept of "AI will replace us all."
Bottom line: a layer of AI Native people is already forming, and it will most likely grow. And that's genuinely interesting.
