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docs/how-to/sequential-process.mdx

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+---
+title: Sequential Processes
+description: A comprehensive guide to utilizing the sequential processes for task execution in CrewAI projects.
+icon: forward
+---
+
+## Introduction
+
+CrewAI offers a flexible framework for executing tasks in a structured manner, supporting both sequential and hierarchical processes. 
+This guide outlines how to effectively implement these processes to ensure efficient task execution and project completion.
+
+## Sequential Process Overview
+
+The sequential process ensures tasks are executed one after the other, following a linear progression. 
+This approach is ideal for projects requiring tasks to be completed in a specific order.
+
+### Key Features
+
+- **Linear Task Flow**: Ensures orderly progression by handling tasks in a predetermined sequence.
+- **Simplicity**: Best suited for projects with clear, step-by-step tasks.
+- **Easy Monitoring**: Facilitates easy tracking of task completion and project progress.
+
+## Implementing the Sequential Process
+
+To use the sequential process, assemble your crew and define tasks in the order they need to be executed.
+
+```python Code
+from crewai import Crew, Process, Agent, Task, TaskOutput, CrewOutput
+
+# Define your agents
+researcher = Agent(
+  role='Researcher',
+  goal='Conduct foundational research',
+  backstory='An experienced researcher with a passion for uncovering insights'
+)
+analyst = Agent(
+  role='Data Analyst',
+  goal='Analyze research findings',
+  backstory='A meticulous analyst with a knack for uncovering patterns'
+)
+writer = Agent(
+  role='Writer',
+  goal='Draft the final report',
+  backstory='A skilled writer with a talent for crafting compelling narratives'
+)
+
+# Define your tasks
+research_task = Task(
+  description='Gather relevant data...', 
+  agent=researcher, 
+  expected_output='Raw Data'
+)
+analysis_task = Task(
+  description='Analyze the data...', 
+  agent=analyst, 
+  expected_output='Data Insights'
+)
+writing_task = Task(
+  description='Compose the report...', 
+  agent=writer, 
+  expected_output='Final Report'
+)
+
+# Form the crew with a sequential process
+report_crew = Crew(
+  agents=[researcher, analyst, writer],
+  tasks=[research_task, analysis_task, writing_task],
+  process=Process.sequential
+)
+
+# Execute the crew
+result = report_crew.kickoff()
+
+# Accessing the type-safe output
+task_output: TaskOutput = result.tasks[0].output
+crew_output: CrewOutput = result.output
+```
+
+### Note:
+
+Each task in a sequential process **must** have an agent assigned. Ensure that every `Task` includes an `agent` parameter.
+
+### Workflow in Action
+
+1. **Initial Task**: In a sequential process, the first agent completes their task and signals completion.
+2. **Subsequent Tasks**: Agents pick up their tasks based on the process type, with outcomes of preceding tasks or directives guiding their execution.
+3. **Completion**: The process concludes once the final task is executed, leading to project completion.
+
+## Advanced Features
+
+### Task Delegation
+
+In sequential processes, if an agent has `allow_delegation` set to `True`, they can delegate tasks to other agents in the crew. 
+This feature is automatically set up when there are multiple agents in the crew.
+
+### Asynchronous Execution
+
+Tasks can be executed asynchronously, allowing for parallel processing when appropriate. 
+To create an asynchronous task, set `async_execution=True` when defining the task.
+
+### Memory and Caching
+
+CrewAI supports both memory and caching features:
+
+- **Memory**: Enable by setting `memory=True` when creating the Crew. This allows agents to retain information across tasks.
+- **Caching**: By default, caching is enabled. Set `cache=False` to disable it.
+
+### Callbacks
+
+You can set callbacks at both the task and step level:
+
+- `task_callback`: Executed after each task completion.
+- `step_callback`: Executed after each step in an agent's execution.
+
+### Usage Metrics
+
+CrewAI tracks token usage across all tasks and agents. You can access these metrics after execution.
+
+## Best Practices for Sequential Processes
+
+1. **Order Matters**: Arrange tasks in a logical sequence where each task builds upon the previous one.
+2. **Clear Task Descriptions**: Provide detailed descriptions for each task to guide the agents effectively.
+3. **Appropriate Agent Selection**: Match agents' skills and roles to the requirements of each task.
+4. **Use Context**: Leverage the context from previous tasks to inform subsequent ones.
+
+This updated documentation ensures that details accurately reflect the latest changes in the codebase and clearly describes how to leverage new features and configurations. 
+The content is kept simple and direct to ensure easy understanding.