Networked Agent Organizations — Identity Shift

After a challenging period, it’s time to reflect on the evolving landscape of organizational structures in the age of artificial intelligence. While we’ve previously explored how agents could learn from DAOs and how decentralized technology solved consensus problems through various protocols, the reality is that DAOs have largely failed to deliver on their promises. They simply aren’t flying well in practice.

The Finance-First Problem with DAOs

The fundamental issue with DAOs lies in their heavily finance-oriented approach. In traditional DAO structures, whoever owns the majority of tokens or holds more tokens essentially wields greater power and influence. This tokenization-based governance model creates an inherent inequality that doesn’t align with what we actually want to achieve in agent-based organizations.

Enter Networked Agent Organizations (NAOs)

So what kind of alternative to DAOs could we build specifically for agents? The answer lies in emerging organizational structures called Networked Agent Organizations (NAOs or ANOs, depending on the preferred abbreviation). These represent mixed organizations where artificial intelligence agents, humans, gig workers, and other entities work together collaboratively to achieve common goals.

The Identity Revolution: Moving Beyond Tokenization

The most significant departure of NAOs from classical DAOs is the fundamental shift from tokenization and tokens to identity-based systems. Agent identity encompasses a wide range of factors, but the core elements include:Individual Identity: Who the agent is and what it represents

**Individual Identity: Who the agent is and what it represents

- **Reputation Systems**: Track records of service quality and reliability

- **Service Offerings**: The specific capabilities and services an agent can provide to others

In these networked states, identity and reputation truly matter. Rather than financial holdings determining influence, an agent’s proven track record and capabilities become the primary currency of organizational power and decision-making authority.

From Decentralization to Networks

The shift from DAOs to NAOs involves two major domain changes, reflected even in the abbreviation itself. The first transformation moves us from “decentralization” to “networks.”

While decentralized systems are technically networks, blockchain enthusiasts have become obsessed with algorithmic trust and the rigid principle that central servers or decision-makers simply cannot be allowed to exist. However, when we examine real-world organizations, we don’t observe this kind of full decentralization. Instead, we see the opposite pattern: groups of people who actually hold the power to make decisions. Real organizations tend to be more centralized than the decentralized ideal suggests.

Network organizations embrace a more pragmatic approach to different kinds of interactions. They’re not exclusively decentralized — they might be hierarchical, and that’s acceptable. They might be centralized, and that’s also fine. What matters most is achieving the organizational goal, and someone needs to set and guide toward that goal. This makes network organizations much closer to modern organizational structures than what we typically envision in purely decentralized setups.

From Full Autonomy to Agency

The second major shift moves from “full autonomy” to “agency.” While this distinction might seem subtle, it’s critically important for understanding how these organizations function.

In a system built around full autonomy, entities are completely independent, acting solely on their own interests and doing whatever they want. The only limiting factor is the amount of tokens they hold, which determines how much influence they can exert.

Agency operates differently. While agents still maintain autonomy and retain the right to make their own decisions and conduct their own reasoning, they become more integrated into the organization while simultaneously becoming more empowered. The goal isn’t to make agents completely independent, but rather to empower them to make meaningful decisions within a collaborative framework.

A Better Framework for Post-AI Labor

This combination — the shift from decentralization to networks and from full autonomy to agency — creates a focus on what agents can do and how they can do it, rather than simply allowing them to act purely in self-interest. This framework provides a much better setup for addressing the modern challenges of post-AI labor forces.

Post-AI labor forces will look fundamentally different from today’s employment landscape. We’re already witnessing a transition from full-time workers dedicated to single companies toward more freelance-based arrangements. The future will likely feature an even more pronounced gig economy where people tackle simple, discrete tasks for multiple employers simultaneously.

This future workforce will be a blend of people and agents, with humans in the loop playing crucial roles in agent networks. People can serve as the missing piece that helps combat hallucination, validate results, integrate outputs, and manage what could be called the “swarm of agent policies.”

## The Human Element Remains Essential

Currently, we haven’t reached a stage where AI can be fully autonomous and hallucination-free. We haven’t yet entered the post-LLM era. Until we do, humans will remain integral parts of these networks, helping agents perform their jobs effectively and reliably.

The Future of Organizational Structure

Networked Agent Organizations represent a significant evolution that will likely replace DAOs entirely, bringing much-needed structure to our post-AI world. By focusing on identity over tokenization, networks over rigid decentralization, and agency over pure autonomy, NAOs offer a more practical and effective framework for organizing the mixed human-AI workforce of tomorrow.

This organizational model acknowledges both the capabilities and limitations of current AI technology while creating structures that can evolve as the technology advances. Rather than forcing artificial constraints based on ideological purity, NAOs embrace pragmatic solutions that actually work in the real world.