---
title: Workflows
subtitle: Workflows are systems that execute tool calls in a sequence
slug: guides/agents/architectures/workflows
---

Workflows execute predefined sequences of tool calls with LLM-driven decision making. Use the `workflow_agent` agent type for structured, sequential processes where you need deterministic execution paths.

Workflows are stateless by default but can branch and make decisions based on tool outputs and LLM reasoning.

## Agents vs Workflows

**Agents** are autonomous systems that decide what tools to call and when, based on goals and context.

**Workflows** are predefined sequences where the LLM follows structured paths (for example, start with tool A, then call either tool B or tool C), making decisions within defined branching points.

The definition between an *agent* and a *workflow* is not always clear and each can have various overlapping levels of autonomy: workflows can be made more autonomous by structuring the decision points to be highly general, and agents can be made more deterministic by adding tool rules to constrain their behavior.

## Workflows vs Tool Rules

An alternative to workflows is using autonomous agents (MemGPT, ReAct, Sleep-time) with [tool rules](/guides/agents/tool-rules) to constrain behavior.

**Use the workflow architecture when:**
* You have an existing workflow to implement in Letta (e.g., moving from n8n, LangGraph, or another workflow builder)
* You need strict sequential execution with minimal autonomy

**Use tool rules (on top of other agent architectures) when:**
* You want more autonomous behavior, but with certain guardrails
* Your task requires adaptive decision making (tool sequences are hard to predict)
* You want to have the flexibility (as a developer) to adapt the level of autonomy (for example, reducing constraints as the underlying LLMs improve)

## Creating Workflows

Workflows are created using the `workflow_agent` agent type.
By default, there are no constraints on the sequence of tool calls that can be made: to add constraints and build a "graph", you can use the `tool_rules` parameter to add tool rules to the agent.

For example, in the following code snippet, we are creating a workflow agent that can call the `web_search` tool, and then call either the `send_email` or `create_report` tool, based on the LLM's reasoning.

<CodeGroup>
```python title="python" maxLines=50
from letta_client import Letta

client = Letta(token="LETTA_API_KEY")

# create the workflow agent with tool rules
agent = client.agents.create(
    agent_type="workflow_agent",
    model="openai/gpt-4.1",
    embedding="openai/text-embedding-3-small",
    tools=["web_search", "send_email", "create_report"],
    tool_rules=[
        {
            "tool_name": "web_search",
            "type": "run_first"
        },
        {
            "tool_name": "web_search",
            "type": "constrain_child_tools",
            "children": ["send_email", "create_report"]
        },
        {
            "tool_name": "send_email",
            "type": "exit_loop"
        },
        {
            "tool_name": "create_report",
            "type": "exit_loop"
        }
    ]
)
```

```typescript title="node.js" maxLines=50
import { LettaClient } from '@letta-ai/letta-client'

const client = new LettaClient({ token: "LETTA_API_KEY" });

// create the workflow agent with tool rules
const agent = await client.agents.create({
    agentType: "workflow_agent",
    model: "openai/gpt-4.1",
    embedding: "openai/text-embedding-3-small",
    tools: ["web_search", "send_email", "create_report"],
    toolRules: [
        {
            toolName: "web_search",
            type: "run_first"
        },
        {
            toolName: "web_search",
            type: "constrain_child_tools",
            children: ["send_email", "create_report"]
        },
        {
            toolName: "send_email",
            type: "exit_loop"
        },
        {
            toolName: "create_report",
            type: "exit_loop"
        }
    ]
});
```

```bash title="curl" maxLines=50
curl -X POST https://api.letta.com/v1/agents \
     -H "Authorization: Bearer $LETTA_API_KEY" \
     -H "Content-Type: application/json" \
     -d '{
  "agent_type": "workflow_agent",
  "model": "openai/gpt-4.1",
  "embedding": "openai/text-embedding-3-small",
  "tools": ["web_search", "send_email", "create_report"],
  "tool_rules": [
    {
      "tool_name": "web_search",
      "type": "run_first"
    },
    {
      "tool_name": "web_search",
      "type": "constrain_child_tools",
      "children": ["send_email", "create_report"]
    },
    {
      "tool_name": "send_email",
      "type": "exit_loop"
    },
    {
      "tool_name": "create_report",
      "type": "exit_loop"
    }
  ]
}'
```
</CodeGroup>