How will AI Agents transform the world? And why do they need to be Decentralized?

This episode explores the frontier of AI agents—their power, their risks, and their role in shaping our future, on THE PEOPLE'S AI, presented by Gensyn. Host Jeff Wilser talks with Shaw Walters (founder of Eliza Labs) and Harry Grieve (co-founder of Gensyn) about what happens when AI agents become autonomous, self-coding, and capable of running their own workflows or even companies.

Shaw explains how Eliza Labs is building an operating system for AI agents that can write plugins, make decisions, and operate independently. Harry walks through how Gensyn is creating a decentralized infrastructure for machine learning verification, allowing trust to be cryptographically enforced.

Together, they discuss:

• Why “agent swarms” may soon outnumber human teams
• How cryptographic trust can secure AI systems
• Whether AI agents will replace white-collar jobs
• What a decentralized, AI-native internet might look like

We also dig into philosophical questions: Who governs these agents? What does it mean to build trust in autonomous systems? And what happens to society when the agents are working… for themselves?

About Gensyn:

Gensyn is a protocol for machine learning computation. It provides a standardised way to execute machine learning tasks over any device in the world. This aggregates the world's computing supply into a single network, which can support AI systems at far greater scale than is possible today. It is fully open source and permissionless, meaning anyone can contribute to the network or use it.

Gensyn - LinkedIn - Twitter - Discord

Eliza Labs:

https://www.elizaos.ai/

Should AI be regulated by governments, left to the courts, or guided by open markets and open source? That question is at the heart of this thoughtful, civil debate between two leaders shaping the future of AI policy.

In this episode of The People’s AI, we’re joined by Justin Hendrix (Tech Policy Press) and Jeff Amico (Gensyn) for a wide-ranging conversation on how — and by whom — artificial intelligence should be governed. We explore the competing tensions between innovation and regulation, centralization and decentralization, open models and closed ones.

We cover:

• The case for federal vs. state-level AI legislation
• Whether a moratorium on state AI laws could backfire
• AI’s environmental footprint and the hidden cost of data centers
• National security, China, and the myth of technological containment
• The nuanced risks (and rewards) of open-source AI models

This isn’t a food fight — it’s a conversation grounded in substance, disagreement, and common ground.

Timestamps:

• (2:03) What is Gensyn? What is Tech Policy Press?
• (4:16) Defining the guests’ north stars for AI policy
• (6:37) Who should set the rules—Congress, states, courts, or global bodies?
• (12:31) The federal bill that may override state AI laws
• (17:22) What exactly should we regulate? Models, data, or applications?
• (24:17) Geopolitics, China, and national security implications
• (30:45) The open-source debate: freedom vs. risk
• (39:08) What keeps them up at night: from monopolies to environmental collapse
• (46:55) Notes of optimism — and what gives them hope

If you’re curious about the future of AI regulation, this is the debate to hear.

Tech Policy Press:

https://www.techpolicy.press/

About Gensyn:

Gensyn is a protocol for machine learning computation. It provides a standardised way to execute machine learning tasks over any device in the world. This aggregates the world's computing supply into a single network, which can support AI systems at far greater scale than is possible today. It is fully open source and permissionless, meaning anyone can contribute to the network or use it.

Gensyn - LinkedIn - Twitter - Discord

What if we could trust AI results the way we trust cryptographic signatures? That’s the radical promise behind Gensyn’s work—building verifiable, decentralized AI infrastructure from the ground up.

We kick off Season 2 of The People’s AI with Ben Fielding and Harry Grieve, the co-founders of Gensyn. We hear how their origin story began in a London warehouse—right before COVID lockdown—and how their mission has evolved from federated learning for tier-one banks to a sweeping new protocol for decentralized machine learning computation.

In this episode, we dig deep into:

• Why decentralized AI is technically hard to pull off — and why Gensyn is focused on solving it
• The limitations of vertical scaling, and how “horizontal scaling” might change everything
• What determinism really means in ML, and why it’s essential for verification and trust
• The nuance behind hallucinations in GenAI — and why they’re not always a bug
• How agentic systems and a “machine economy” might transform our future interactions

We also explore how their work connects to AI arbitration, smart contracts, and the growing demand for trustless execution across compute environments.

This is one of those conversations where infrastructure, philosophy, and future vision converge. We’re excited to share it with you.

About Gensyn, presenting partner of The People's AI Season 2:

Gensyn is a protocol for machine learning computation. It provides a standardised way to execute machine learning tasks over any device in the world. This aggregates the world's computing supply into a single network, which can support AI systems at far greater scale than is possible today. It is fully open source and permissionless, meaning anyone can contribute to the network or use it.

Gensyn - LinkedIn - Twitter - Discord