SelfManaged Crew

FlowHunt’s SelfManaged Crew lets you create teams of AI agents with roles and tasks, managed by an AI manager, to tackle complex projects collaboratively and efficiently.

SelfManaged Crew

SelfManaged Crew

AI crews allow you to use entire teams of AI agents to perform complex tasks. It may initially seem confusing, but the crew approach simply copies how real teams work. In any given team, you’ll have individuals with unique roles and skills, working together to reach a common goal.

Advanced blog generator Flow with SelfManaged Crew

Let’s say you want to create and publish a long-form blog post. The work usually starts with an SEO specialist researching keywords and outlining the content. They’ll create an SEO brief, which will be passed on to the content writer. Once the writer is done, their colleague will proofread and edit the article to ensure quality. What about the featured images or infographics? A designer will help with that.

You already have at least three or four people working on creating this piece of content. They share a common goal, but each specializes in something else and performs a different subtask. Let’s see how you can copy this team as a group of AI agents.

Curious about the Flow we’re analyzing in this guide? It’s the Advanced Blog Generator and you can easily find it in your Flow library.

What Is The SelfManaged Crew Component

The SelfManaged Crew component is a structural component that groups agents and tasks into one team led by a manager agent. It only represents one group, allowing you to create multiple agent teams within a single Flow. The core of creating an AI crew is setting up agents and their tasks.

SelfManaged Crew component settings

The Role of AI Agents in Crews

The SelfManaged Crew component is only a structural component bringing groups of agents together. Because of this, the first step to successfully using AI Crews is understanding and setting up individual agents, including the manager agent.

AI Agents are computer programs that can perform tasks and solve problems independently. They process information and take action based on their programming, knowledge, and goals.

AI agent component settings

Agents aren’t just generative AI. Given the right tools, they can perform real tasks like sending emails, creating documents, and more. Instead of pre-defining rigid triggers for this behavior, Agents can decide independently.

In practice, you no longer need to give detailed prompts for a rigidly controlled generative behavior. All you need to do is provide an agent with their role, personality, and goal, ensuring they know who they are and what motivates them.

Learn more about AI agents and how to use the AI Agent component

How Are Crews Better Than Single Agents?

If there’s an issue in your team’s processes, you can quickly pinpoint the issue and work with a competent team member to find a solution. Now imagine it’s just you working on the entire task, and the issue arises in your own mind. That’s much harder to notice and pinpoint. The same happens when comparing a single agent with a crew of agents.

When prompting a single agent, you give it a complex task with little to no control over how individual subtasks are performed. When doing complex tasks, this can lead to bottlenecks and low output quality.

With a crew, you can split the main task into specific subtasks, assigning each to a unique AI team member. The result is a much more professional and detailed output. It also means easier debugging, and lastly, coordinating specialized agents allows you to handle much more complex tasks.

The Difference Between Self-Managed and Sequential Crews

You might have noticed there are two different Crew components in your dashboard. The difference between these types of crews is in the order of tasks and the level of control you get.

Let’s go back to our marketing team example. The first agent in line would be the SEO specialist. Once the topic is researched, it forwards the information to the content writer. Below, you can see how the SEO Agent’s task is connected to the Writing task of the Content Writer Agent:

The two crew components side to side

Let’s talk about a Sequential Crew first. With a Sequential Crew, the tasks are performed one after another in the exact order you specify in the Flow. Once a task is done, it’s permanent, and the Flow moves on to the next agent. That is great for straightforward processes or processes that require less computational power.

Let’s focus on a real-life content writer. They will first do research and move on to writing, but as the article unfolds, they may realize more research is needed. Understandably, they will go back and forth between research and writing tasks before finally moving on to the next step. The sequential crew won’t do this. Once a task is done, it’s just done. That’s where Self-Managed crews come in.

With a Self-Managed Crew, the manager AI agent decides the order of tasks and how many iterations are needed. When making decisions, the AI tries to copy traditional organizational hierarchies closely. This opens up the possibility of repeating tasks and creating multiple iterations of the final output.

Thanks to the manager LLM that delegates tasks and oversees their execution, the SelfManaged Crew can work with a single complex task. The manager LLM can seamlessly split the task and assign subtasks to the correct agents. This is especially great when you know what needs to be done, but you’re not sure about the exact process and subtasks.

How To Use SelfManaged Crews

The SelfManaged Crew is a structure component that brings agents and task components together in a group. To use a SelfManaged Crew, we need to first define the manager agent, the team members, and their tasks. Only then can we make them a team.

Setting up SelfManaged Crews consists of four steps:

  1. Setting up individual AI Agents
  2. Giving agents tasks
  3. Setting up the manager agent
  4. Making the agents a SelfManaged Crew
The three steps to using agent crews

Setting Up Individual AI Agents

Each member of a real team has a role, goals, and a unique backstory that includes their past experiences, personality, and specific style. So does each AI Agent.

Setting up individual AI agents

For example, let’s focus on the content writer team member:

  • The Role: Your agent’s job title. In this example, being a content writer is the role.
  • The Goal: What the agent does and what their ideal outcome is. The expected outcome for the content writer is a well-written article that adheres to the theme and SEO brief.
  • The Backstory: Represents who the agent is. Whether you like it or not, you always bring your personality, way of thinking, vocabulary, and past experiences to anything you do. This is even more visible in creative work, such as content writing.

Repeat this process for all the agents you want to use in your team.

Learn more about AI agents and how to use the AI Agent component

Giving Agents Tasks

Continuing with our blog creation example, we now know who our agent is. The next step is to let the agent know their task and introduce them to the team.

What Are The Task Components?

In Crews, each Agent is assigned a task to perform. Like in a real team, each member can carry out various project-specific tasks. The task components allow you to specify and assign these tasks.

You’ll notice that, like with the Crew component, there are two possible task components—sequential and SelfManaged. Since these are two opposite approaches to managing agents, mixing them would make no sense. That’s why we’ll also use SelfManaged Tasks when using a SelfManaged Crew:

Task Components

If you have a task in mind but are unsure how to split it into smaller subtasks, simply write it all into a single task. The manager LLM is there to assign tasks and oversee the process, ensuring each agent knows what to do and when. It can split the main task and assign the parts to the correct agent.

In addition to the task, each agent in a Crew can also get appropriate tools, making their job easier and more accurate. In our example, the researcher uses the GoogleSearch and URL Retriever tools to control the research options.

Next, set up the tasks. Each SelfManaged Task must either have a description, the expected output, or both:

The task description for the content writer agent might go a little something like this:

“Given the SEO content brief, write a blog post in no more than 1500 words. 

Never start paragraphs with vague statements such as “In the fast-changing field of…”. Always go directly to the main information the paragraph should deliver. “

Let’s take a closer look at this task description:

  • Given the content brief” – The agent knows what to do with the previous output.
  • Write a blog post of up to 1500 words” – The output we expect from the agent.
  • Never start…..” – Additional custom instructions to tweak the output. These instructions can be any pointers on language, vocabulary, structure, or anything else that will help the agent create what you need.

The expected output field is optional and works great when you need a structured output or make sure something is included in the output. For example, our SEO researcher agent’s task is to create:

A brief in this form:

SEO friendly Title:

SEO friendly Meta description:

SEO friendly Outline

Frequently asked questions

What is the SelfManaged Crew component in FlowHunt?

The SelfManaged Crew component allows you to group multiple AI agents with unique roles and tasks into a team managed by an AI manager agent. This structure mimics real-life teams for better task delegation, iteration, and collaboration on complex workflows.

How does a SelfManaged Crew differ from a Sequential Crew?

A Sequential Crew performs tasks in a strict order you define, with each step completed once before moving on. A SelfManaged Crew, managed by a manager agent, can dynamically decide the order and number of iterations for tasks, enabling more flexible and iterative workflows.

Why use multiple AI agents in a crew instead of a single agent?

Using a crew lets you split complex tasks among specialized agents, improving output quality, enabling easier debugging, and allowing you to tackle more involved projects—just like in real teams.

How do I set up a SelfManaged Crew in FlowHunt?

Set up individual AI agents with defined roles and goals, assign each agent a task, create a manager agent, and connect all agents and tasks within the SelfManaged Crew component. The manager agent will then oversee the workflow automatically.

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