Vibe Coding: Build the Tower Before You Write the Code
A practical way to understand vibe coding: see software as a tower of connected systems, then let AI handle more of the detailed construction while you direct the architecture.
Artificial intelligence, machine intelligence, and the emerging systems that are changing how humans think, create, decide, and interact with machines.
A practical way to understand vibe coding: see software as a tower of connected systems, then let AI handle more of the detailed construction while you direct the architecture.
AI can create extraordinary abundance while changing the economic value of human work. The deeper question is not only what AI can produce, but who will own, earn and participate in the economy it creates.
A practical AI–human protocol for designing intelligent infographics: build the grayscale architecture first, preserve meaningful fills, then add minimal contextual colour only where it improves clarity.
If extraordinary AI tutoring becomes available to everyone, education may need to move beyond information transfer toward curiosity, exploration, judgment and the development of individual intellectual maps.
The same AI can affect different thinkers in very different ways. It may encourage convergence in predictive use while helping generative users explore a much larger space of ideas.
As AI and machines become more capable, the old relationship between population and productive capacity may be changing.
If AI can provide extraordinary knowledge and tutoring on demand, education may shift from training workers toward training minds, curiosity, judgment and lifelong learning.
A thought experiment about whether a persistent AI system could develop a self—and whether an external observer could ever know if experience emerged.
AI is making many cognitive tasks dramatically faster—but repeated exposure may also distort how humans perceive time, effort, productivity and the difficulty of thinking.
AI is strongest when a problem is already sufficiently represented. The real world is harder when the information needed to solve the problem has not yet been discovered.
What if an intelligent AI could expose a real but weak vulnerability, causing humans to spend their limited defensive resources patching the wrong problem?
AI may remove much of the cognitive heavy lifting without removing work. The emerging advantage may come from designing workflows in which humans and AI agents work together reliably.
Superintelligence can optimize extraordinarily well, but it still operates inside a feasible domain defined by physics, resources, information, time and other constraints. The domain defines the function.
AI doom can be real without every AI-doom narrative being reliable. The Cute Tiger Cub Problem examines how satire, music, borrowed authority and visual certainty can blur the line between evidence, interpretation and speculation.
