I was using sub-agents wrong... Here is my way after 20+ hrs test

Summary

This video explores the use of sub-agents within the cloud code framework, focusing on how they optimize performance by improving context management and task delegation. The presenter shares personal insights on the challenges and best practices for using sub-agents, particularly in managing token consumption and enhancing coding workflows. They discuss how specialized sub-agents can be created for various services (e.g., Versel, Chassen) and integrated into project development. Key strategies include efficient context sharing, task delegation, and ensuring each sub-agent focuses on research and planning, not direct implementation. The video also touches on real-world applications and optimization techniques.

Takeaways

• 😀 Sub-agent feature introduced in cloud code is designed to improve context management and token optimization, but it initially led to negative experiences such as slowness and high token consumption.
• 😀 The main purpose of the sub-agent system is to delegate tasks like file reading and code analysis to a secondary agent, saving tokens and improving efficiency by reducing context loss during large file operations.
• 😀 Sub-agents work best when used for research tasks and providing summaries, rather than for direct implementation, to avoid issues of limited context and poor performance.
• 😀 Each agent in the sub-agent system has limited context, leading to challenges when trying to fix bugs, as agents don’t share full context of previous tasks.
• 😀 Context optimization is crucial for maximizing the effectiveness of sub-agents. Saving context in separate files (e.g., MD files) and retrieving them later is a best practice for keeping all agents on the same page.
• 😀 Specialized sub-agents can be created for specific tasks like frontend or backend development. These agents are loaded with domain-specific documentation to improve accuracy and efficiency.
• 😀 Optimizing context sharing across agents, like through task folders and local MD files, has significantly improved the success rate of cloud code execution.
• 😀 In addition to basic research, specialized agents (e.g., Versell AI SDK expert, Chassen frontend expert) are designed to handle service-specific documentation and provide implementation planning based on project context.
• 😀 The best practice for sub-agent tasks is to provide agents with clear output formats and rules, ensuring they follow specific processes like reviewing context files before and after performing tasks.
• 😀 Sub-agents should never execute implementation directly but focus on designing and proposing plans, ensuring the parent agent has full context and is able to execute tasks accurately without context loss.
• 😀 With the proper setup and tools, like specialized MCP tools for component retrieval, sub-agents can assist in high-fidelity UI design and SDK integration, creating detailed plans for implementation while updating the overall project context.

Q & A

What is the main purpose of the sub-agent feature introduced by Cloud Code?

The sub-agent feature was introduced to optimize context management and token usage in Cloud Code. It helps to delegate tasks to specialized sub-agents, reducing the load on the parent agent by limiting the amount of context stored in the conversation history.

What were the initial issues users faced with sub-agents when they were first introduced?

Users initially found the sub-agent feature to be slow, consuming more tokens than expected, and not contributing significantly to improved results, which led to a negative experience.

How does Cloud Code manage token usage with the sub-agent feature?

By assigning specific tasks to sub-agents, the parent agent only sees a summary report from the sub-agent rather than the entire task execution. This reduces token consumption as it avoids including large amounts of context in the conversation history.

Why does the parent Cloud Code agent have limited information about the sub-agent's tasks?

The parent agent only knows that a task has been assigned to the sub-agent and receives a summary of the sub-agent's work. It does not have direct access to the detailed actions performed by the sub-agent, limiting its ability to track what has been done.

What challenges arise when trying to use sub-agents for both research and implementation tasks?

When sub-agents are tasked with both research and implementation, the parent agent can struggle with bugs or errors in the implementation. The lack of full context about previous actions makes it difficult for the parent agent to fix issues effectively.

How can context sharing across agents be improved for better collaboration?

One solution is to use a file system as a central context management tool. By saving task results and research reports into local files, agents can retrieve the relevant context as needed, ensuring all agents are on the same page.

What role do specialized sub-agents for specific services (e.g., Vercel, Stripe) play?

Specialized sub-agents are designed to have expert knowledge of specific services, such as Vercel AI SDK or Stripe, including documentation and best practices. These sub-agents assist in making implementation decisions by analyzing the codebase and generating implementation plans tailored to each service.

How does the process of setting up a specialized sub-agent for a service like Vercel AI SDK work?

To set up a specialized sub-agent, you first define the system prompt with relevant documentation for the service. You then configure the sub-agent with tools (e.g., MCP tools) to access the latest documentation and implement best practices specific to the service, such as Vercel AI SDK v5.

What improvements were made to the context management system during the creation of sub-agents?

Improvements included the use of a file system to store context outside of the conversation history. This system stores task-related data in local files, which can be retrieved by agents to maintain context across different stages of the task, ensuring that agents don't lose track of important information.

What is the significance of having a goal defined for each sub-agent?

Having a defined goal for each sub-agent ensures that the agent focuses on delivering a specific outcome, such as designing a plan or conducting research, without directly executing the implementation. This helps maintain clarity in task delegation and ensures that sub-agents work within predefined boundaries.