> ## Documentation Index
> Fetch the complete documentation index at: https://docs.firebender.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

> Coordinate specialized AI agents to handle complex tasks

## Concurrent coding agents

Firebender offers simple primitives to do this:

|                                         | Isolation             | When to use                                                                                                                                |
| --------------------------------------- | --------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
| **[Tabs](/input/chat/tabs)**            | None (same directory) | Lightweight and good for changes in completely different files, or for read-only operations like exploring the codebase                    |
| **[Worktrees](/multi-agent/worktrees)** | Full (worktrees)      | Independent features/PRs that can have conflicts and you don't want affecting your cwd. Auto heals from conflicts from the configured base |
| **[Subagents](/multi-agent/subagents)** | Managed by AI         | Complex tasks where you want Firebender to delegate focused work in separate contexts                                                      |

If done well, your overall throughput of *good* changes increases dramatically: `Zone of productivity`.

## Common pitfalls

### Parallelization overhead

**Problem**: Conflicts, higher error rates, and context-switching costs can eat into productivity gains.

**Solution**:

* Use **[Worktrees](/multi-agent/worktrees)** for isolated changes that auto-heal merge conflicts from base
* Use **[Subagents](/multi-agent/subagents)** when you want the main agent to delegate focused work in parallel
* Prefer smaller, narrowly-scoped tasks: they have the highest merge rate and lowest context-switching cost
* **[Subagents](/multi-agent/subagents)**: create focused callable agents for operational tasks like verification, PR review, or doc sync

<Info>
  Focused subagents scoped to specific tasks dramatically improve accuracy. Create your own with `/agent` or see [Subagents](/multi-agent/subagents).
</Info>

### Staying in flow

**Problem**: Managing AI agents can feel like being an engineering manager: frequent context switches, waiting on slow responses, and forgetting your original intent ("doorway effect").

**Solution**:

* **Write, Ask, and Plan modes**: switch between implementation, read-only exploration, and planning as the task evolves
* **[Plan mode](/multi-agent/planning)**: AI researches approaches and asks clarifying questions before coding
* **[GLM 4.7](/get-started/models)** and **[GPT-5.2](/get-started/models)**: fast agentic models for quick iteration
* **[Commands](/input/commands)**: quickly insert pre-written prompts or task descriptions you use often

<Info>
  Use `/help` to quickly create a command based on a previous chat. See [Commands](/input/commands).
</Info>