Agent Orchestration: Hierarchical Delegation & Persistent Agents

Hey guys! Let's dive into a really cool feature request that could seriously level up Claude Code. We're talking about making our agents way more autonomous and capable of handling complex tasks. Think of it like building an AI development team – super exciting, right?

The Problem: Why We Need More Agent Power

Right now, our subagent system is like a good first step, but it's got some limitations. It's set up in a "hub-and-spoke" way, meaning the main Claude Code instance can tell subagents what to do, but those subagents can't delegate tasks to others. This creates a few headaches:

1. Limited Autonomy: The Manual Taskmaster

With the current setup, tackling any complex, multi-stage task feels like you're stuck playing project manager. For example, if you ask Claude Code to implement a new feature, you've got to manually break down the problem and call on different agents one by one. Where's the magic of a truly autonomous agent that can take a complex goal and run with it from start to finish?

2. Lack of Modularity: The Monolithic Agent Menace

This limitation often forces us to create these massive, monolithic subagents. Imagine one agent trying to handle everything – backend, frontend, database, testing – all within a single context. It's a recipe for chaos! These agents become hard to maintain, reuse, and scale. We need to think smaller, more specialized agents for a more modular approach.

3. Context Pollution: The Cluttered Mind

Picture this: the main agent's context window gets bogged down with the nitty-gritty details of every sub-task. It's like trying to keep a high-level focus on a project when your brain is crammed with every tiny detail. This context clutter can seriously reduce the agent's ability to stay focused on the overall objective.

4. No Long-Running Tasks: The Here-and-Now Agent

The current model is transactional – agents jump in for a specific task and then vanish. There's no way to launch an agent to handle persistent, long-running background tasks. Think about cool stuff like monitoring logs or watching a repository for new pull requests – features that are impossible right now.

The Solution: Hierarchical Delegation and Persistent Agents

So, how do we fix this? I'm proposing a major upgrade to our agent framework with two key features: Hierarchical Delegation and Persistent, User-Initiated Agents. These enhancements will empower Claude Code to tackle complex projects with true autonomy and efficiency.

1. Hierarchical Agent Delegation: Agents Managing Agents

This is the heart of the idea! Imagine subagents that can invoke and manage other subagents. We're talking about building a hierarchical or networked structure, just like a real-world development team. This approach could revolutionize how we handle complex projects.

Here's how we could make this happen:

• Give the Task tool to all subagents: This simple change would allow them to delegate tasks just like the main agent can. It's all about empowering our subagents.
• Enable a "manager" or "orchestrator" agent pattern: Think of an agent that receives a high-level goal, crafts a plan, and then uses the Task tool to delegate sub-tasks to specialized "worker" agents. This creates a clear division of labor and expertise.
• Support both synchronous and asynchronous delegation: A manager agent should be able to wait for the result of a child agent's task or launch multiple agents in parallel to tackle different parts of a problem at the same time. This parallelism could significantly speed up project completion.
• Allow the manager agent to receive and synthesize results: Imagine the manager agent collecting the work from all the child agents and weaving it into a final, polished solution. This integration capability is crucial for complex projects.

2. Persistent, User-Initiated Agents: Agents That Stick Around

To give you guys more direct control and support for those long-running tasks, we need a new set of agent management capabilities.

• Direct Agent Launch: Let's introduce a slash command that allows users to directly invoke a specific agent with a prompt, bypassing the main agent's conversational flow. It's about giving users more control.
  • Example: /launch <agent-name> [prompt] (e.g., /launch code-reviewer "Check my recent changes for security flaws.")
• Persistent Background Agents: Let's extend the /launch command to support long-running, background agent sessions that don't block the user's terminal. This is key for tasks that need continuous attention.
  • /agents-ps: A command to list all currently running persistent agent sessions and their status. Transparency is crucial.
  • /agent-attach <session-id>: A way to connect to a running agent's session to see its live output and interact with it. Real-time monitoring and interaction.
  • /agent-kill <session-id>: A command to terminate a running agent session. Easy termination for clean management.

Use Case Examples: Putting It All Together

Let's look at a couple of examples to see how these features would work in the real world.

Use Case 1: Autonomous Full-Stack Feature Implementation

Imagine a user prompts:

> Use the 'feature-lead' agent to implement a new user dashboard as described in JIRA-123.

Here's how the magic could happen:

1. The top-level feature-lead agent springs into action. It uses another agent to read the Jira ticket and comes up with a plan. Smart planning is the first step.
2. It then orchestrates a team of specialized agents in parallel:
   • Task(prompt="Design and write the database schema migration for dashboard analytics", subagent_type="db-architect-agent") Database design handled by the expert.
   • Task(prompt="Create secure backend API endpoints to serve the dashboard data", subagent_type="api-developer-agent") Secure APIs are crucial.
   • Task(prompt="Build the frontend dashboard UI in React based on the Figma mockups", subagent_type="ui-specialist-agent") A beautiful and functional UI.
3. As the api-developer-agent finishes its code, it can invoke another, more granular agent: Task(prompt="Review the new API endpoints for security vulnerabilities and adherence to our style guide", subagent_type="code-reviewer-agent"). Ensuring code quality and security.
4. The feature-lead agent keeps an eye on the progress, integrates the work from all the child agents, and delivers the final, tested, and reviewed feature. Seamless integration and delivery.

Use Case 2: Proactive Codebase Monitoring

Let's say a user wants an agent to continuously monitor their repository.

1. The user runs: /launch pr-watcher-agent "Watch for new PRs in this repo and post initial feedback based on our style guide in CLAUDE.md" Launching the watcher.
2. The pr-watcher-agent starts up as a background process. The user can keep working without interruption. Background magic.
3. The user can check on the agent's status by running /agents-ps. Keeping tabs on things.
4. When a new PR is opened, the agent autonomously performs its review task, demonstrating a proactive, long-running capability that is not possible today. Proactive and persistent monitoring.

Alternatives Considered: Why This Is the Best Path

We've thought about other ways to tackle this, but they just don't stack up.

• Creating larger, monolithic agents: This is the current workaround, but it's less scalable, harder to maintain, and doesn't encourage reusing specialized agent skills. Not the sustainable solution.
• Manual user-driven orchestration: Requiring the user to manually chain agent commands in a single, complex prompt is inefficient, brittle, requires constant intervention, and defeats the purpose of an autonomous system. Too much manual labor.

Why This Matters: The Transformative Potential

This set of features would be a transformative step for Claude Code. It would elevate it from a powerful pair-programmer to a true agentic system capable of managing complex projects like an AI development team. This is the future.

Here's why it's so important:

• Enable Greater Complexity: It would allow the autonomous handling of large-scale, multi-faceted software engineering challenges. Tackling the big stuff.
• Promote Modularity: It would encourage the creation of small, focused, and reusable specialist agents. Building a toolbox of experts.
• Improve Context Management: It would isolate sub-tasks into their own context windows, keeping the primary conversation focused and efficient. A clear and focused mind.
• Unlock New Capabilities: It would enable proactive, long-running tasks like monitoring, CI/CD integration, and automated code maintenance. The possibilities are endless.

In essence, this is about making Claude Code a truly autonomous and powerful tool for software development. Let's make it happen, guys!