When intelligence becomes abundant

The first time I used ChatGPT seriously was a little over two years ago. What surprised me wasn’t that it could answer questions. Google had already been doing that for years. What changed was the way I could interact with knowledge.

For a long time, when I wanted to understand something new, the process was fairly predictable. I would open dozens of tabs, read articles, compare sources, and take notes. It could take days, sometimes weeks, before I had enough context to write or think clearly about a subject.

With ChatGPT, a different dynamic appeared. Learning started to feel more like a conversation. Through prompts I could explore ideas, go deeper into topics, and structure my thinking in minutes. What once required long, scattered searches became a much more direct process.

Soon after, I began using it for something closer to my daily work: data. I discovered that I could build analyses, interpret information, and even design conceptual models simply by conversing with the system and feeding it structured inputs. My interaction with information began to change. Artificial intelligence was no longer just answering questions. It was starting to participate in the process of thinking.

Over time that presence began to appear in other parts of everyday life. When I bought my Tesla, for example, I started talking with Grok during my drives to work. What used to be quiet moments or time spent listening to music became long conversations about technology, history, economics, or whatever idea happened to cross my mind. Artificial intelligence began occupying spaces that once belonged to solitary thought.

Something similar began happening in the technical world. Tools like Claude are starting to reduce the distance between having an idea and being able to implement it. For decades there was a clear boundary between imagining a system and actually building it. Programming required a specialized technical layer. That boundary is beginning to thin. It is increasingly possible to describe an idea and watch it turn into code, models, or working systems.

Artificial intelligence becomes a layer between thought and execution. And that shift doesn’t stop at software development. It is also beginning to reshape how the internet itself is organized.

For years search engines prioritized pages optimized for algorithms. Today many AI systems actively look for content produced by human communities. Platforms like Reddit have become valuable sources of information precisely because the content comes from real conversations between people.

In an environment where automated content generation will become increasingly common, human signals start to gain a different kind of value. Within a few years, a large share of what we see on the internet will likely be produced by artificial intelligence: texts, images, analyses, recommendations.

Intelligence itself is becoming abundant.

For centuries producing knowledge was difficult. Writing a thoughtful text, developing an idea, or constructing an analysis required time, experience, and concentration. That effort created scarcity.

Artificial intelligence reduces that scarcity. And when something becomes abundant, its value shifts.

Value begins to move elsewhere.

Toward lived experience, real conversations, communities formed around shared interests, and judgment shaped by experience rather than calculation alone.

In that environment, the human begins to function as a signal. A signal that carries origin, context, and history.

The most profound change brought by artificial intelligence may not be automation or the transformation of industries. It may be something more cultural.

A world where intelligence becomes abundant may ultimately increase the value of what remains deeply human.

The question is no longer simply how much machines can do.

The question becomes something else.

What it means to remain human in a world where thinking is no longer an exclusively human activity.