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An agent in Layest is an autonomous AI worker that executes tasks on your behalf — answering questions, processing data, calling integrations, and taking actions without requiring manual intervention for every step. Each agent you create has its own model, instructions, tools, and memory, making it purpose-built for the job you need done. This guide walks you through creating and deploying your very first agent from scratch.

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What is a Layest Agent?

A Layest agent combines a large language model (LLM) with a set of instructions, tools, and integrations to act as a reliable, repeatable worker inside your workspace. Agents can be triggered manually, by an event, or on a schedule — and every run is logged so you can inspect inputs, outputs, and any errors that occurred.
You do not need to write code to create an agent. The Layest dashboard provides a fully visual configuration experience. Code-level customization is available for advanced use cases.

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Before You Begin

Make sure you have:
  • A Layest account with at least one workspace created
  • Access to the Agents section in the left-hand navigation
  • (Optional) A clear idea of what task your agent will handle

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Creating Your First Agent

1

Navigate to the Agents section

In the Layest dashboard, click Agents in the left-hand sidebar. This opens your agent list — it will be empty if this is your first time here.
If you belong to multiple workspaces, confirm you are in the correct workspace before proceeding. The workspace name is displayed in the top-left corner of the dashboard.
2

Click 'New Agent'

Click the New Agent button in the top-right corner of the Agents page. A modal will appear prompting you to choose a starting point.
3

Choose a template or start from blank

You have two options:
  • Agent Library — browse pre-built templates for common use cases such as customer support, data extraction, and research. Starting from a template gives you a pre-filled set of instructions and tools that you can customize.
  • Blank Agent — start with a clean slate and configure everything yourself.
For this guide, select Blank Agent to learn each configuration option step by step.
If you already know your use case, check the Agent Library first. A template can save significant setup time and shows you best-practice instruction patterns.
4

Configure the name, description, and model

Fill in the Basic Info fields:Next, select a Model from the dropdown. If you are just getting started, the default model is a good choice. You can change this at any time.
Different models have different costs and rate limits. Higher-capability models (such as GPT-4o or Claude 3.5 Sonnet) produce better results but consume more credits per run. Review your plan limits before selecting a model for high-volume workflows.
5

Write your system instructions

The Instructions field is where you define your agent’s persona, role, and behavior. This is the system prompt that the model receives before every conversation or task.A clear, specific instruction set leads to much better agent behavior. Here is a simple example:
Keep your instructions focused. Overly long or contradictory instructions can confuse the model and lead to inconsistent behavior. Start simple and iterate.
6

Save and activate your agent

Click Save Agent at the bottom of the configuration panel. Your agent is now created in a Draft state.To make it available for runs and triggers, toggle the status from Draft to Active using the switch in the agent header.
Draft agents can be tested manually from the dashboard but will not respond to external triggers or scheduled runs. Activate your agent only when you are satisfied with its configuration.

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Testing Your Agent

Once your agent is active, you can send it a test message directly from the dashboard:
  1. Open your agent from the Agents list.
  2. Click the Test tab in the agent panel.
  3. Type a message in the chat input and press Send.
  4. Review the agent’s response and inspect the run log for details.
The test panel shows the full input/output alongside any tool calls the agent made, making it easy to debug instructions before connecting your agent to live workflows.

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Next Steps

Now that your agent is running, explore these topics to unlock its full potential:

Agent Configuration

Deep-dive into every configuration option — models, memory, tools, and behavior settings.

Agent Library

Browse pre-built templates to find a starting point for common use cases.

Run Workflows

Learn how to run your agent manually, via triggers, or on a schedule.

Observability

Monitor agent runs, inspect logs, and track performance over time.