Single Agents vs Agent Squad
In Orkeia, AI agents can operate in two main ways:- Single Agent
- A unique agent that performs all steps of the task.
- Centralizes reasoning and maintains consistency in the flow.
- Agent Squad
- A set of specialized agents that work collaboratively.
- Each agent focuses on a part of the task, delivering results that others can consume.
When to Use a Single Agent?
Using a single agent is recommended in scenarios where:- The task is simple and can be solved in one or a few steps.
- It’s important to save tokens and reduce operational cost.
- There’s no need for specialized roles (e.g., doesn’t need separate “researcher”, “analyst”, and “writer”).
- The flow should be fast, with minimal latency.
- Answering direct customer questions in a chat.
- Generating quick summaries of short texts.
- Executing direct commands, like “convert this file to PDF”.
When to Use an Agent Squad?
The squad is more suitable when:- The task requires role division (research, analysis, decision, writing, validation).
- There’s a need for specialization, where each agent has distinct instructions and knowledge.
- The problem is complex or open-ended, requiring multiple steps to reach a robust answer.
- The flow needs cross-verification, increasing consistency and quality.
- Scalability is desired: different agents can run in parallel on subtasks.
- Creating extensive reports with data collection, statistical analysis, and final writing.
- Customer service with agents taking on different roles (triage, resolution, follow-up).
- Research projects with agents specialized in sourcing, validating information, and generating synthesis.
- Long workflows that require step orchestration.
Comparative
| Criterion | Single Agent | Agent Squad |
|---|---|---|
| Complexity | Low, direct tasks | High, open-ended and multi-phase tasks |
| Speed | Faster, low latency | May be slower, due to coordination |
| Cost (tokens) | More economical | Higher cost, multiple agents processing |
| Consistency | Linear flow, no multiple views | Possibility of divergence, but with cross-checking |
| Specialization | Single profile | Each agent can be specialized |
| Scalability | Limited to the reasoning of one model | Scalable with division of parallel subtasks |
| Use Example | Answering simple FAQ questions | Producing detailed analytical reports |
Best Practices
- Assess complexity before deciding: if the task can be solved by a single agent, prefer simplicity.
- Use squads only when necessary: the overhead of coordination and cost only pays off in complex scenarios.
- Define clear roles: each agent in the squad should have well-defined responsibilities, avoiding redundancy.
- Monitor costs: distribute token usage among agents in a controlled manner.
- Keep interaction logs: for squads, the history helps debug coordination failures.
Final Summary
- Single Agent is ideal for quick, direct, and economical tasks.
- Agent Squad is the right choice for complex problems that require collaboration, specialization, and orchestration.