Why Not Ask AI?
The Rapid Acceleration
For the past four years, the world has been captivated by AI. Venture capital is chasing AI startups, social feeds are filled with constant updates, and newsletters bombard our inboxes daily. Incremental optimizations to foundational models and frequent fine-tuned updates are released at a relentless pace, introducing tools that were unimaginable until recently. AI empowers smart engineers to become even more productive while eliminating repetitive tasks much like heavy machinery replaces manual labor while keeping the operator in control. Few-shot learning, persistent memory, skills, tools, and mechanisms such as KV-cache transfer are coming together to make AI systems increasingly capable and cheaper of performing tasks at a superhuman level.
A Shift in Perspective
This era recalls the editor, programming language, browser, and framework wars of the past decade. However, while I actively participated in those earlier tech shifts, the current AI movement feels fundamentally different. Its sheer velocity is overwhelming, resembling a massive ship approaching the shore that quickly expands beyond one's field of view before there is time to fully process or explore it. Although I utilize tools like Claude and Codex on a daily basis, I feel far more comfortable as a consumer of AI rather than trying to grasp its inner workings.
Depending on whom you ask, AI can be described as a multivariable function that predicts the next token, a deep neural network, or even an artificial brain. But beyond how we define AI, conversational interfaces are fundamentally disrupting the way we interact with software. Why search through menus for an option when you can simply type or speak what you want? As a result, established tools are increasingly taking a back seat. Traditional web search can now be replaced by asking a question directly, and even things like slide decks, reports, and other forms of content can be generated effortlessly through a simple prompt.
Impact on Creativity and the Mind
The traditional craft of coding now faces an uncertain future, raising broader questions about what lies ahead for other creative and intellectual fields writing, editing, storytelling, graphic design, video production, and beyond. Instead of working through iterative two-week creation cycles, we can now generate dozens of possibilities almost instantaneously. The bottleneck is shifting from creating options to choosing, refining, and directing them. Whether audiences will be able to distinguish the work of an original creator from that of a skilled imitator remains uncertain.
Perhaps AI will ultimately force original creators to adapt, experiment, and continuously raise the quality of their work. Yet beneath all of this lies a more fundamental question: what happens to the satisfaction and intellectual thrill of solving a difficult problem ourselves? There is a particular reward in struggling with a problem, finally understanding it, and producing something with our own hands and minds. If machines increasingly take over that struggle, will we lose something meaningful or will we simply find new problems worthy of that same intellectual effort?
Perhaps there is an even bigger societal question. If technology can dramatically reduce the scarcity of skilled intellectual labour, does this bring us closer to a form of socialism that was previously impractical? Not socialism through the redistribution of human labour, but through the possibility that productive capability itself becomes abundant and widely accessible.
If one person with AI can accomplish what once required an entire team of specialists, the traditional relationship between skill, labour, scarcity, and economic value begins to change. The question then becomes not simply who owns the machines, but what happens to a society when the productive power once concentrated in highly skilled individuals becomes available to almost everyone.
Society may adapt to this transition much as hunter-gatherers once transitioned into farming. The thrill of the hunt and the prowess of the master hunter gradually gave way to the expertise of the farmer, where different skills became valuable and different people were celebrated. Later, farmers gave way to industrialists, engineers, and creators.Throughout history, new competencies have repeatedly replaced old ones. Each transition has changed not only how we work, but also what we value. So what will be displaced this time?
If intuition is one of the highest forms of human intelligence, could AI allow us to evolve into more intuitive beings? And, more importantly, how do we turn intuition into meaningful work? Could it mean becoming better stock pickers, better engineers who can detect bugs before they happen, or better scientists who can identify promising directions that would otherwise take years to discover? These possibilities become increasingly plausible when machines can process vast numbers of data points and perform complex, multi-scenario analyses far beyond the capacity of an individual human mind.
Perhaps the real opportunity is to use it to expand the scale of problems we can tackle. Could humans spend more of their time solving problems such as clean energy, climate change, pollution, hunger, water scarcity, unity and inequality ? Can AI eradicate the need to go to war ? Or will we simply pause, waiting for AI to figure out the solutions for us?
As I write this post, AI is helping me refine my raw thoughts, polish my phrasing, and turn scattered ideas into something far more readable, allowing me to articulate my ideas with an ease I’ve never experienced before. Yet this very convenience leaves me wondering: am I still leading my own train of thought, or is AI gradually shaping it for me? And perhaps the most ironic question is the simplest one: how should I title this post? Why not ask AI?