AgentsAgents

Agents

Learn how named AI Agents in Giga combine role, instructions, context, Skills, and Connections.

An Agent is a named, reusable AI role in Giga.

Agents are useful when you want Giga to operate with a consistent role, instructions, context, and access across repeated work.

Video placeholder

Agents overview video.

What an Agent can bring together

The exact capabilities available to an Agent depend on the current workspace, Group, Connections, Skills, and live tool surface.

When to use an Agent

Create or use an Agent when you want a reusable AI role that people can return to repeatedly.

Examples include:

  • a sales research Agent
  • a recruiting Agent
  • a customer support Agent
  • an operations Agent
  • a finance reporting Agent

A normal Chat works well for ad hoc work that does not need a persistent named role.

Agent vs Chat vs Skill vs Workflow

PrimitiveBest fit
ChatDirect, ad hoc work with Giga
AgentA named reusable AI role
SkillReusable instructions for a specific kind of task
WorkflowA reusable ordered multi-step process
PulseRecurring scheduled work

These primitives can work together.

For example, a recruiting Agent might use a candidate-screening Skill, work through a Workflow, and run recurring work through a Pulse when the live configuration supports it.

Where Agents live

Agents operate within Giga’s Group permission model.

The Group helps determine who can access the Agent and which shared resources are in scope.

That means an Agent’s availability can depend on:

  • the Group it belongs to
  • the user’s Group membership
  • the Connections available in that scope
  • the Skills available to the Agent
  • the current live permissions

Learn about Sharing Agents →

Agent instructions

An Agent can have durable instructions that shape how it behaves across repeated work.

Those instructions can define things such as:

  • its role
  • its responsibilities
  • preferred ways of working
  • constraints
  • terminology
  • expected output style

Keep durable Agent behavior in the Agent’s instructions rather than re-explaining it in every Chat.

Learn about Agent instructions →

Agents and context

Agents can also have durable context relevant to their role.

The live Giga environment determines what context and resources the Agent can actually retrieve.

Giga should never assume an Agent has access to every Track, Connection, file, or piece of company context simply because those resources exist in the workspace.

Learn about Agents and context →

Agents and Connections

Connections let an Agent work with live external systems.

For example, an Agent might be allowed to use:

  • a CRM
  • an analytics platform
  • a support tool
  • an internal database
  • an MCP server

The Agent can only use Connections that are available within its current configuration and permission scope.

Learn about giving Agents access to Connections →

Agents and Skills

A Skill gives Giga reusable instructions for a specific kind of task.

An Agent can use Skills when the live Agent and Skill configuration makes those Skills available.

For example:

This keeps the Agent’s identity separate from the reusable task method.

Agents and Pulses

The current Pulse model can target an Agent.

That means recurring scheduled work can run through a named Agent when the live Pulse configuration supports it.

For example, a reporting Agent could run a recurring weekly check through a Pulse.

Learn about Pulses with Agents →

A simple example

Imagine your Sales team creates a Sales Research Agent.

The team gets a consistent AI role they can return to, while access remains controlled by the workspace and Group permission model.

Image placeholder

Diagram showing an Agent at the center with Role + Instructions, Context, Skills, Connections, Group permissions, and Pulses around it.

Explore Agents