# Create your first agent


# Create your first agent

This is the end-to-end path for building an AI voice agent: create it, configure the builder tabs, test it in voice and chat, then publish. Each tab has its own deep-dive page — this one ties them together in the order you'll actually work through them.

## Before you start

- You need an account with permission to build agents — an **organization admin** or a **project manager** for the project. See [roles](../organization-login#roles-and-permissions).
- Decide which **project** the agent belongs to, since the project sets the timezone and locale. See [Projects](../organization-login#projects).

## Step 1 — Create the agent

![The Agent tab](/img/screenshots/portal/agent-tab.png)
*The Agent tab: name, project, description, system prompt and the live prompt-strength analysis.*

Open the agent builder at **/agent/setup** and start on the **Agent** tab. This is where the agent's identity *and* the words it says live.

1. Give the agent a clear **name**.
2. Add a short **description** of what it does.
3. Choose the **use case** that matches your goal.
4. Pick a **template** to start from, if one fits — templates pre-fill sensible settings you can change later.
5. Write the **system prompt** — the core instruction set that defines who the agent is and what it must do.
6. Set the **greeting** (the first line when a call connects) and the **end**, **fallback**, **busy** and **voicemail** messages.

Save to create the agent. You can now move through the rest of the tabs.

:::note[The prompt and messages live on the Agent tab]

The system prompt, greeting and key messages are all on the **Agent** tab — not the **Behavior** (Engine) tab. That tab tunes *pacing* (interruptions, silence, filler words), not what the agent says.

:::

## Step 2 — Configure the core tabs

Work down the tabs, saving as you go. You don't need every tab for a first version — the four below are the essentials.

### Language model

On the **[LLM](./llm)** tab (labeled **Model** in the builder), first choose the **voice pipeline mode** (it drives the whole call), then pick the LLM **provider and model**, set temperature, token limits and a fallback model. This decides how the agent reasons and how consistent it sounds.

### Voice and audio

On the **[Voice & audio](./voice-audio)** tab, choose how the agent listens and speaks: pick a **speech-to-text** provider and model and a **text-to-speech** provider, model and voice, then tune the provider-specific controls.

### Conversation behavior

On the **[Engine](./engine-behavior)** tab, tune *pacing*: barge-in and interrupt handling, voice-activity-detection padding, response delay, silence handling and filler words. The system prompt, greeting and messages are set back on the **Agent** tab.

### Calling

On the **[Calling](./calling-telephony)** tab, set inbound and outbound use, maximum call duration, auto-hangup, assigned numbers and webhooks. (Call transfer is configured separately, via the Tools → Workflow "Transfer Call" function.)

## Step 3 — Add knowledge and tools (optional)

Once the basics sound right, make the agent more capable:

- **[Knowledge & RAG](./knowledge-rag)** — on the **Model** (LLM) tab, turn on RAG, link a knowledge base so the agent answers from your own documents, and tune similarity and top-k.
- **[Tools & MCP](./tools-mcp)** — give the agent functions, connect MCP servers, and design call flows in the Workflow Builder so it can take real actions during a call.

:::tip[Build in layers]

Build in layers. Get the voice and greeting right first, confirm it in a test, then add knowledge and tools. It's much easier to tell what changed when you add one capability at a time.

:::

## Step 4 — Test the agent

Try the agent before it touches real calls. The Portal gives you two test surfaces:

- **Voice test** at **/agent/interface** — talk to the agent and hear it respond with the voice and behavior you configured.
- **Chat test** at **/agent/chat** — exchange text turns to check the prompt and logic quickly, without using voice.

Iterate: adjust a tab, save, and test again until it sounds and behaves the way you want.

## Step 5 — Publish and put the agent to work

When the agent passes your tests, publish it. Publishing isn't a separate flow — on the **Agent** tab, turn on the **Published** toggle (and make sure the **Active** toggle is on too). A published, active agent is ready to be used on real calls. From there:

- point a **[campaign](../campaigns)** at it to run outbound calls, or
- assign it to handle **inbound** calls (see [Calling & telephony](./calling-telephony)).

Every call the agent handles is recorded and analyzed in [Call logs & analytics](../call-logs), where you'll find the recording, transcript, AI summary and sentiment to guide your next round of tuning.

## Next steps

- [Configure the LLM](./llm)
- [Set up voice and audio](./voice-audio)
- [Shape conversation behavior](./engine-behavior)
- [Run a campaign with your agent](../campaigns)