Build your first agent
Build your first agent
10 min
Gaëlle Caplier1. How to build a custom AI agent?
1.1. The components of a custom AI agent
A custom agent is made of several components:
- A name, which you will use to call it in your conversations
- ⚠️ The name needs to be unique on the workspace
- ⚠️ Your company may have some specific naming standards for your agents: check out the name formats in your agent library!
- Custom instructions, where you define exactly what the agent should do, which role it should take, which output it should produce, etc.
- The underlying AI model, which you can pick in a large list of available LLMs.
- Knowledge sources, where you will select which data sources your agent can leverage to answer user queries.
- Capabilities, which are the “superpowers” of your agent. You can allow it to take actions for you - like browsing the web, drafting emails in your inbox, updating fields in your CRM, and more!
1.2. The agent builder
When you start creating a new agent, you will be brought to the agent builder interface. It is made of four main sections, which map to the main components of a custom agent.
In the Instructions section, you will write your custom instructions.
- 📚 Instructions are written in natural language, but there are some best practices to follow to write effective custom instructions. Check them out!
- 💡 You can use AI to help you refine your instructions! Check out available agents on your workspace: is there one to help you write instructions? At Dust, we call that agent the
promptWriter, but yours may have a different name.
The Advanced button above the Instructions box will let you change the underlying AI model used by your agent, if you wish.
Below instructions, you have the Spaces section.
This section will only be relevant if you are a member of a restricted space, e.g. a space that contains private data that your administrator has decided to only open to a specific set of Dust users. How do you know if that's your case? Simply click on Manage: if there's nothing to select here, then you don't have access to any restricted space, and you don't need to change anything in your agent!
Below, you have the Capabilities and Knowledge section. This is where you're going to pick what data your agent can access, and which actions it can take. We'll cover how to add knowledge and capabilities to your agents in the next chapters of this course.
Then, you'll find the Triggers section, where you can choose to automate your agent. We will cover this in the next course, feel free to ignore this section for now.
Finally, the last section in the agent builder is the Settings, where you'll choose a name for your agent, a description, and you'll define its sharing parameters. An Unpublished agent is only available to you, its creator. Keep your agents unpublished during their testing phase. Once an agent is ready to be released and used by your colleagues, switch it to Published to open it to everyone on the workspace.
You can also add some tags to organize your agent library, and make other colleagues editors of your agent.
1.3. In action - Building a search agent
2. When should you create a custom agent?
As you've seen in previous courses, there are a lot of use cases you can address simply with the @dust agent or the @deep-dive agent, which are available by default on your Dust workspace. If you need those agents to have extra capabilities, you can always add them manually in the context of your conversation.
So when do you actually need to create a custom agent? The key word here is recurrence.
- For any kind of recurring task, you will want to create a custom agent, because it will always know what to do and how to address your specific needs thanks to its custom instructions. You will not need to provide context again and again with each new conversation.
- For any kind of one-time task, simply talking to
@dustor a similar agent is more than enough!
And how about the case when you started from a one-time task, had a long discussion with
@dust that evolved into a more and more complex and high-value use case, and you would like to package that one into a new custom agent? In this case, you can simply ask @dust at the end of your conversation to give you recommendations on how to transform the conversation into a new custom agent!Test Your Knowledge
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