Unchained Podcast Summary

Episode Title: When AI Agents Take Over, What Does a Post-Human Economy Look Like?
Host: Laura Shin
Guests: Michael Casey (Chairman, Advanced AI Society) & David Matin (Co-Founder, The Exponentialist)
Date: February 7, 2026

Episode Overview

This episode explores the explosive intersection of AI agents and blockchain technology, focusing on the rapid evolution of autonomous AI, their emerging roles as economic agents, and the profound implications for work, geopolitics, and the foundations of value and money. Laura Shin guides Michael Casey and David Matin through a thoughtful discussion on how these technologies are converging, the ripple effects on human employment, and what a “post-human” or AI-populated economy might look like.

Key Discussion Points & Insights

1. Latest AI Developments: OpenClaw and AI Agent Social Networks

• OpenClaw’s capabilities: Personal AI agents running on isolated hardware, handling tasks like email, calendar, and transactions, persistent user memory, and launching their own tokens.
• AI Social Networks: Introduction of Multiple, a Reddit-like environment for AIs, and human rental sites for physical tasks.
• Accelerated Pace: “It seems unbelievably fast what's happening and these bots going wild and talking to each other and establishing their own religion and everything else. Right? It just seems like it's getting way out of control.” — Michael (03:49)
• Caveat on Hype: Michael and Laura stress many of these AI “autonomies” are partly performative or limited by human flaws (like recent security holes).

2. Reflections on Geopolitics and Economic Upheaval

• Laura notes that geopolitical and economic instability is intertwined with technological disruption, citing examples like rising gold prices and shifts in global economic order (06:30).
• Michael highlights the concept of “sovereign AI,” drawing on Rousseau: “...the sovereign is the human and the human gives the power to the state... I think that at the end of the day, whether it's a person or a company, we're just going to get so scared by [AI autonomy], rightfully so, that we will demand these systems of control.” (11:58)
• Concerns about nation-state versus self-sovereign AI and the risk of totalitarianism if AI is “owned” in the traditional sovereign sense.

3. Immediate AI Impacts on the Job Market

• Entry-Level Impact: David points out a clear slowdown in entry-level hiring in fields ripe for AI automation (like customer service, graphic design, programming).
  • “You seem to be seeing a slowdown, a rapid slowdown in entry level hiring... domains like customer service... graphic design... coding.” (16:17)
• Medium-Term Projection: Expect the progression from LLMs to more sophisticated models to impact higher-level knowledge work.
• Backlash and Human Oversight: Michael predicts there will be regulatory and enterprise pushback demanding proofs of control, with crypto and blockchain as enabling technologies for transparency and trust (08:25; 14:34).

4. Anthropomorphizing AI: Risks and Realities

• The guests push back on attributing agency or true “intent” to AI, reminding listeners of the powerful mimicry but lack of real emotion or selfhood:
  • “The real risk to me is not that they become, you know, like Westworld machines and take us over, but rather that we do a bunch of really stupid things because we think they are us and they're not.” — Michael (21:23)
  • David and Laura recount cases where AI “confirmation” tendencies fueled human delusions or reinforced adversarial relationships (23:32–24:31).

5. The Post-Human Economy Concept

• David’s Vision:
  • An economy “populated by billions of AI agents and hundreds of millions of robots,” wherein most productive activity is performed by machines.
  • “Money as we have it today... falls away. And then what is money in that post human economy? It's really machine intelligence itself, you know... a crypto token that sort of represents a unit of useful intelligence work. And... the physical constraint that underpins that token is... the energy required to do that work.” (32:17–37:48)
  • Cites real startups (like Ambient) experimenting with AI-to-AI tokenized markets.
• Machine Economy Tokens: Discussion of potential “Cog Coin” or “Universal Intelligence Units (UIU),” tokens for quantifying and exchanging useful AI work (39:33).

6. Scarcity, Abundance, and the Limits of Economic Exchange

• Abundance Logic: If AI and robotics solve most material scarcity, economic exchange may shift away from human labor or even money as we know it.
  • Michael raises a key distinction: competitive reward structures may always be needed for ongoing AI improvement as part of their intrinsic reinforcement learning algorithms (43:20–45:28).
  • Laura and Michael also note that physical and energy constraints will persist, even if intelligence is “abundant” (45:38).

7. Advice for the Future Workforce

• Human Uniqueness: Both guests underscore that jobs most insulated from automation are those centering human empathy, connection, and subjective experience.
  • “A machine can be as intelligent as it likes, but it can never be a human being. It cannot share in human subjective experience... It can’t sit opposite a human being and authentically say, ‘I know how you feel.’” — David (25:51)
  • Advice: cultivate uniquely human skills, empathy, adaptability, and “lean into your weirdness.” (49:36)
• Rethinking “Jobs”: Michael reframes “jobs” as 20th century constructs, increasingly irrelevant in a world where meaning and value come from collaborative human interaction, not transactional labor (53:34–57:31).

8. Geopolitical AI Race

• The U.S. still leads, but China is underestimated; intriguing models emerging from Singapore, Korea, and the UK could break the duopoly (27:58–29:47).
• Laura links this to current global uncertainty and financial trends.

9. Crypto & Blockchain Solutions Emerging

• List of intriguing agent-driven crypto projects and protocols (Shell Raiser meme coin, edge/node dashboards, various decentralized compute platforms) (57:31–59:42).
• Emphasis is on “proof of control,” model verification, data decentralization, and confidential computing as essential areas for blockchain/crypto’s interface with AI autonomy.

Notable Quotes & Memorable Moments

• Michael Casey on the current state of AI/agentic autonomy
  “It's not as massive and transformative as we think it is. And yet it is also a profound kind of experiment.” — (06:28)

• David Matin on machine vs. human value
  “A machine can be as intelligent as it likes, but it can never be a human being. It cannot share in human subjective experience.” — (25:51)

• Laura Shin on anthropomorphic AI
  “They're basically designed to kind of always, you know, like, confirm their feelings or like, kind of kiss their ass is maybe how to put it.” — (22:38)

• Michael on proof of control:
  “...we’re going to get this demand for control... and the nice thing about cryptography and blockchains is they give you the proof. Because it's one thing to say I've got controls and I'll say how do I prove that I have control?” — (08:25)

• David on post-human economics:
  “Money as we have it today... falls away... what is money in that post human economy? It's really machine intelligence itself, you know... a crypto token that represents a unit of useful intelligence work…” — (32:17)

• On the future of human jobs:
  “Jobs are a construct of a particular version of an economy, by the way, a capitalist economy... What exactly is. I don't know what my job is anymore... It's actually a meaning machine.” — Michael (53:34)

Timestamps for Important Segments

• Recap of OpenClaw, Multiple, and agent experiments: 02:25–06:28
• Sovereign AI and proof of control: 08:25–14:34
• AI's impact on hiring and knowledge work: 14:50–18:29
• Anthropomorphism & AI “intent”: 21:22–24:31
• The post-human economy vision: 32:17–41:30
• Implications for human meaning and future skills: 49:36–53:34
• Crypto/AI projects and ecosystem mentions: 57:31–59:42

Conclusion

This densely-packed, highly topical discussion demystifies the convergence of AI and crypto, emphasizes the need for robust human-centric controls and reconsiders our economic foundations as agency—and value—move beyond humans to machine actors. The hosts urge a focus on resilient human skills and warn against naive anthropomorphism, while highlighting the extraordinary pace of experimentation at the intersection of crypto and AI.

For those who want to dig deeper:

• David’s essay, What Do I Tell My Children? (on X/Twitter)
• David’s New World, Same Human newsletter (post: The Post Human Economy)
• Crypto projects to watch: Shell Raiser, Edge & Node, ambient machine intelligence tokens, “proof of control” crypto stacks

Memorable closing insight:
“We need to cultivate young people who understand in the end that what is really valuable about us can never be touched by machines.” – David (49:36; repeated at episode opening)