Every era is shaped by its "miracle material." Steel forged the Gilded Age, semiconductors lit the digital age, and now AI has arrived as the "Infinite Mind." History says: whoever masters the material defines the era.
The future is hard to predict because it always disguises itself as the past. Early phone calls were as brief as telegrams; early films looked like filmed stage plays. As Marshall McLuhan said: "We always drive into the future using the rearview mirror."
Today's AI chatbots are essentially imitating the Google search box of the past. We're in that awkward transitional period that every major new technology goes through.
Why is AI harder to apply to general knowledge work?
Compared to coding agents, knowledge work is more fragmented and harder to verify.
1. Context Fragmentation: A programmer's tools and context are typically concentrated in an IDE. General knowledge work is scattered across dozens of tools.
2. Lack of Verifiability: Code can be verified through tests. But how do you verify that a project is being managed well?
Steel and Steam
Ivan analogizes organizations to steel and steam.
Steel is the first metaphor — AI is the steel of organizations, with the potential to maintain contextual consistency across an entire workflow.
The steam engine is the second metaphor — companies today are still in the "replace the waterwheel" phase, jamming AI chatbots into existing tools. When old constraints disappear, we should reimagine what organizations should look like.
