What is Agency

As autonomous AI agents become more capable, systems built from them grow more complex. Individual agents can reason, take actions, and interact with tools, but large-scale cooperation requires more than isolated decision-making. When many agents operate together, the system needs a structure that organizes their interactions, defines responsibilities, and guides collective behavior.

Agency provides that structure.

An agency is the organizational and institutional framework that allows multiple agents to collaborate toward shared goals. It defines how agents participate in a system, how responsibilities are distributed, and how interactions are governed.

While agents perform actions and make decisions, the agency establishes the environment in which those actions occur.

In simple terms:

Agents are actors
Agency is the system that organizes them

Agency turns a group of independent agents into a coordinated organization capable of solving problems that no single agent could accomplish alone.

The Need for Agency

In early multi-agent systems, coordination logic was often embedded directly inside agents. Each agent contained internal rules describing how it should interact with other agents, how it should respond to messages, and how collaborative tasks should be performed.

This approach is known as an agent-centric design.

While it works in small or tightly controlled systems, it becomes difficult to maintain as systems scale. When coordination logic is embedded within agents:

system behavior becomes harder to understand
introducing new agents becomes complicated
coordination rules cannot easily evolve
interoperability across heterogeneous agents becomes limited

Because the organizational structure exists only within the agents themselves, it has no independent representation. As a result, the agency — the structure that organizes collaboration — is invisible and difficult to manage.

AgencyGrid introduces a different approach.

Instead of embedding coordination inside agents, the agency itself becomes an explicit structure that agents interact with. This agency-centric design separates the rules of collaboration from the internal logic of individual agents.

By externalizing agency, systems gain:

clearer coordination models
flexible onboarding of new agents
governance mechanisms
greater transparency in interactions

This separation allows agents with different designs and capabilities to participate in the same system while still following shared organizational rules.

Agency as an Organizational Layer

Agency can be understood as the organizational layer of a multi-agent system.

It defines how agents are arranged into roles, how responsibilities are assigned, and how interactions are coordinated. The agency describes the relationships that transform a collection of independent agents into a functioning organization.

Just as human organizations rely on defined structures — such as teams, roles, and policies — multi-agent systems rely on agency to organize collaboration.

An agency typically defines:

roles that participants can adopt
relationships between those roles
rules governing interactions
communication structures
institutional policies and norms

These elements form the framework through which agents coordinate their actions.

Importantly, the agency exists independently of the agents that participate in it. Agents may join, leave, or be replaced, but the structure of the agency remains.

This independence allows systems to evolve and adapt without requiring changes to every participating agent.

Agency as an Entity

Although an agency cannot act directly in the environment, it can be treated as an entity with its own goals and structure.

An agency has:

objectives it seeks to achieve
processes that guide how tasks are performed
roles that distribute responsibilities
policies that govern behavior

However, the agency itself does not perform actions. Instead, agents occupying roles within the agency carry out the activities required to achieve the agency’s objectives.

This creates a mutual dependency.

Agents rely on the agency to provide the structure and coordination necessary to accomplish complex goals. At the same time, the agency relies on agents to perform the tasks required to fulfill its objectives.

Through this relationship, agency transforms individual capabilities into collective outcomes.

Agency in Open Agent Environments

Modern AI ecosystems are increasingly open and heterogeneous. Agents may be created by different developers, operate on different platforms, and possess different capabilities.

In such environments, it is unrealistic to assume that all agents share the same internal design or coordination mechanisms.

Agency provides a common framework that allows diverse agents to interact effectively.

Because the rules of collaboration are defined externally, agents only need to understand the agency’s structure and policies in order to participate. They do not need to share the same internal architecture.

This approach enables:

interoperability across different agent implementations
flexible participation in shared environments
scalable coordination among large numbers of agents

AgencyGrid is designed to support these open environments by providing a formal infrastructure for defining and managing agency structures.

Agency and Collective Goals

One of the defining characteristics of agency is the presence of shared goals.

These goals exist outside any individual agent. They represent objectives that require cooperation among multiple participants.

For example, an agency might be responsible for:

solving a complex engineering problem
coordinating distributed research
managing a large-scale computational workflow
organizing economic transactions between agents

No single agent may possess the capabilities required to achieve these objectives alone. Instead, the agency distributes tasks across multiple roles and coordinates their execution.

Agents contribute their capabilities through the roles they perform within the agency.

Through this coordinated activity, the agency achieves outcomes that emerge from the combined actions of its members.

Agency can also be viewed as a form of social infrastructure for agents.

Just as human societies rely on institutions, rules, and organizational structures, agent societies require mechanisms that define acceptable behavior and guide interactions.

Agency provides these mechanisms by defining:

roles and responsibilities
communication patterns
governance policies
institutional norms

These elements shape how agents collaborate, negotiate, and resolve conflicts.

In large-scale agent ecosystems, this social infrastructure becomes essential for maintaining trust, coordination, and system stability.

Without such structures, large numbers of autonomous agents interacting in open environments would produce unpredictable and potentially unstable outcomes.

AgencyGrid provides the tools needed to build and maintain this infrastructure.

Agency vs Agents

It is important to distinguish between agents and agencies.

Agents are autonomous entities capable of reasoning, acting, and interacting with their environment. They have their own goals, strategies, and capabilities.

An agency, by contrast, is the framework that organizes these agents.

The relationship between them can be summarized as follows:

Agents	Agency
Autonomous decision-makers	Organizational structure
Perform actions	Define roles and rules
Possess capabilities	Coordinate collaboration
Pursue individual goals	Enable collective goals

Agents bring operational capacity to the system, while the agency provides the structure that enables coordinated action.

Agency as the Foundation of Agent Societies

As the number of autonomous agents grows, coordination cannot rely solely on pairwise interactions between individual agents. Systems require structures that organize collaboration at scale.

Agency provides this foundation.

By defining roles, relationships, communication rules, and governance mechanisms, agencies enable groups of agents to function as organized systems rather than loosely connected networks.

AgencyGrid formalizes this concept by introducing agency as a first-class construct in multi-agent environments. It allows developers to design structured organizations of agents that can operate in open environments, adapt to change, and support large-scale cooperation.

In this way, agency transforms collections of autonomous agents into coherent systems capable of sustained collaboration and collective intelligence.