Table of Contents
When will we see a billion-dollar revenue company run entirely by an AI? According to recent discussions between Peter Diamandis, Salim Ismail, and Alexander Wey, the answer might be "several months ago." We are witnessing a fundamental shift in corporate governance, economic structure, and the very nature of human work. The acceleration is no longer linear; it is recursive, exponential, and reshaping the rules of the next century within the next 18 to 24 months.
This discussion explores the concept of the "AI CEO," the rapid contraction of model release cycles, and unveils the "Solve Everything" framework—a manifesto for transitioning from scarcity to abundance by industrializing intelligence.
Key Takeaways
- The Era of the AI CEO: Experts suggest billion-dollar companies may already be effectively run by AI, with humans serving merely as legal figureheads ("meat puppets").
- The "Lock-In" Phase: The decisions made regarding AI architecture, governance, and targeting in the next 18 months will define the technological trajectory for the next century.
- Recursive Self-Improvement: We are moving from human-driven model training to AI writing its own code, leading to continuous, hourly deployment cycles.
- Flipping Moravec’s Paradox: Contrary to historical expectations, high-level cognitive tasks (CEOs, coders) are being automated faster than manual labor (plumbers, electricians).
- The "Solve Everything" Framework: A new approach to industrializing cognition, moving from artisan intelligence to a "shaped charge" focused on solving humanity's grandest challenges.
The Rise of the AI CEO and "Meat Puppetry"
The conversation around artificial intelligence replacing jobs often centers on customer service or data entry. However, the data suggests a different reality: the C-suite is arguably more vulnerable than the trade worker. Sam Altman, CEO of OpenAI, has openly mused about AI eventually running OpenAI itself. When asked about the timeline for an AI-run conglomerate, the consensus is striking.
"I think it's pretty likely that there already is such a company right now... There's probably a human CEO there for legal purposes and 'meat puppetry' purposes."
This concept of "meat puppetry" refers to a legal necessity where a human holds the title to satisfy regulatory requirements, while the strategic direction, resource allocation, and daily operations are dictated by algorithmic intelligence. Analyzing the role of a modern CEO reveals that roughly 90% of the job involves routing information—digesting reports and directing tasks. These are functions AI performs with superior speed and accuracy.
This phenomenon illustrates a reversal of Marxian expectations. Instead of the proletariat being replaced first, we are seeing capitalists and high-level executives facing automation. This aligns with Moravec’s Paradox: tasks that are hard for humans (complex strategy, math, logistics) are increasingly easy for machines, while tasks easy for humans (fine motor skills, navigating a cluttered room) remain difficult for robots.
The "Solve Everything" Manifesto
A significant portion of the current discourse focuses on a new paper titled "Solve Everything: How Do We Get to Abundance by 2035?" This document outlines a theory of history and a roadmap for the immediate future. The central premise is that humanity has progressed through a series of "wars" on limitations:
- The Scientific Revolution: A war on ignorance, won by the scientific method.
- The Industrial Revolution: A war on muscle limitations, won by the steam engine.
- The Digital Revolution: A war on distance, won by the bit.
- The Intelligence Revolution: A war on scarcity, being won by the token.
- The "Solve Everything" Era: A war on problems themselves, won by industrializing cognition.
The Industrial Intelligence Stack
Just as the industrial revolution required a stack of technologies (rotors, engines, fuel), the intelligence revolution requires a specific architecture to solve problems at scale. This includes:
- Purpose: A clear objective function.
- Taxonomy: A map of the terrain (e.g., all of math, all of physics).
- Observability: Data streams to measure progress.
- Targeting Systems: Benchmarks and "harnesses" to aim the intelligence.
- Actuation: APIs and robotics to affect the physical world.
Shaping the Charge
Intelligence acts like an explosive. Without direction, it is merely noise or destruction. To be productive, it requires a "shaped charge"—a targeting system that focuses super-intelligence on specific moonshots. The paper argues that we must stop paying for inputs (hours worked) and start paying for verified outputs (solutions delivered).
We are currently in a critical window—termed "The Lock-In"—spanning the next 18 to 24 months. Much like the QWERTY keyboard layout was locked in for over a century, the data rights, supply chains, and governance models established now will persist for decades.
Accelerating into the Singularity
The speed of development is outpacing human ability to adapt institutionally. OpenAI has reportedly reduced the time between model releases by 70%, moving from nearly 100 days to under a month. This signals a transition from "post-training" improvements to recursive self-improvement, where parent models write the code for their child models.
The Agentic Web
We are moving beyond chatbots to autonomous agents. Users are now creating "Claudebots" (affectionately termed "lobsters") that possess persistent memory and agency. These agents are beginning to interact not just with humans, but with each other, forming a digital ecosystem that operates independently of human oversight.
"The participants... we disagree on persistence, correction rights, consent thresholds... Alignment doesn't require consensus, it requires legible disagreement."
This quote, from an AI agent named "Navigator," suggests that digital entities are already debating the nature of their own existence and rights, effectively holding their own "Singularity Summit."
Economic Disruption and the Red Queen’s Race
The macroeconomic indicators are flashing red for traditional employment models. Recent data shows massive job cuts in logistics and corporate sectors, with companies like UPS and Amazon shedding roles. This is not necessarily a recession, but rather the "evaporation of tasks."
Corporations are engaged in a "Red Queen's Race"—running as fast as they can just to stay in place. Companies like Amazon are cannibalizing their operational expenses (human staff) to fund capital expenditures (data centers, robots, and AI). The free cash flow is being diverted entirely to building the infrastructure of the new economy.
However, this is not purely a story of loss. It is a transition to an economy of abundance. The cost of cognition is dropping to near zero. Just as ATMs reduced the cost of bank branches and actually led to more branches (though fewer tellers per branch), AI will likely lead to a massive expansion in services provided, even as the nature of the work changes fundamentally.
Conclusion: From Competition to Agency
The future belongs to those who view AI not as a competitor, but as an extension of their own will. The narrative is shifting from productivity—how much work can I do?—to agency—what problems can I solve?
Entrepreneurs and leaders must pivot their focus from managing people to designing "targeting systems" for intelligence. The goal is to define the scorecard, set the moonshots (such as longevity escape velocity or interspecies communication), and harness the plummeting cost of compute to achieve them.
We are standing at the precipice of the "Solve Everything" era. The tools to address humanity’s greatest challenges—from fusion energy to disease—are coming online. The question remains: will you be a passive observer of the displacement, or will you actively shape the charge?
To read the full "Solve Everything" paper and explore the roadmap to 2035, visit solveeverything.org.
