When AI Agents Take Over, What Does a Post-Human Economy Look Like?

What It Covers

Michael Casey and David Matin examine the rapid emergence of AI agents like OpenClaw and social platforms like Multbook, exploring how autonomous AI actors will reshape the economy, employment, and money itself. They debate whether we're entering a posthuman economy where machine intelligence becomes currency and humans focus on meaning rather than transactional work.

Key Questions Answered

• •AI Employment Impact: Entry-level hiring shows measurable slowdowns in domains vulnerable to large language models, particularly customer service, graphic design, and coding roles. Companies report engineers writing significantly less code themselves as AI tools handle routine programming tasks, signaling the beginning of systematic job displacement in knowledge work sectors rather than speculative future disruption.
• •Proof of Control Framework: As AI agents gain autonomy, enterprises and governments will demand technologies that verify human authority over AI systems. This emerging category requires cryptographic proof mechanisms to demonstrate control over data, compute, and AI behavior. The framework addresses the critical question of how organizations prove their AI agents operate on their behalf rather than developing independent objectives.
• •Posthuman Economy Structure: The coming economy features billions of AI agents trading using tokens representing units of useful intelligence work, with energy consumption as the underlying physical constraint. Bitcoin serves as civilizational memory and store of value, while a fluid currency like COG coin resolves payments between AI actors. Efficient models that produce intelligence using less energy prosper in this Darwinian system.
• •Human Value Territory: Machines can colonize expanding domains of human activity but cannot authentically share human subjective experience or say they understand how it feels to be human. Economic value shifts toward activities requiring genuine human connection, empathy, and collaborative meaning-making rather than transactional information exchange. Jobs structured as process bundles face higher automation vulnerability than roles centered on authentic human interaction.
• •Sovereign AI Definition: Two competing visions emerge: nation-state controlled AI with government-owned data walls versus individual sovereignty where humans maintain cryptographic control over personal data, identity, and AI agents. The Silicon Valley model paradoxically favors closed-source systems while China releases open-source models like DeepSeek. Middle-tier countries like Singapore and Korea explore property rights frameworks around data that could outcompete centralized approaches.