Conductor
Claude Code parallelization — run multiple instances simultaneously
Quick Take: Conductor
Conductor is a force multiplier for developers who use Claude Code heavily. It takes the sequential bottleneck of one-task-at-a-time AI coding and turns it into parallel batch processing. The git branch isolation and conflict detection make parallel execution safe. The task definition format is simple enough to learn in minutes. The catch: you need to be a heavy Claude Code user with multiple independent tasks regularly, and your API budget needs to support the parallelism. For its target audience — professional developers doing 5+ AI-assisted tasks per day — Conductor compresses a day of work into a few hours.
Best For
- •Claude Code power users with 5+ independent tasks to parallelize
- •Solo developers clearing issue backlogs
- •Tech leads preparing multi-feature demos under time pressure
- •Open source maintainers batch-processing bug fixes and improvements
What is Conductor?
Conductor is a developer tool that parallelizes Claude Code sessions, letting you run multiple autonomous AI coding agents simultaneously across different tasks. If Claude Code is a single developer you delegate work to, Conductor is a project manager that spins up a team of Claude Code instances, assigns them independent tasks, manages their git branches, and collects the results. The problem Conductor solves is sequential bottlenecking. With Claude Code alone, you work on one task at a time: fix a bug, wait for it to finish, start the next feature, wait again. If you have 8 independent tasks — 4 bug fixes, 2 test coverage improvements, 2 small features — that's a full day of sequential work. Conductor launches all 8 in parallel, each in its own git branch, and they complete in the time it takes the slowest one to finish. A day of work compresses into 1-2 hours. Conductor handles the orchestration that would be painful to do manually. It creates isolated git branches for each task so agents don't step on each other's code. It analyzes task definitions before launch and warns you if two tasks might modify the same files — because parallel agents editing the same file guarantees merge conflicts. It monitors progress across all sessions and aggregates results when they complete: which tasks succeeded, what files changed, which tests pass. You define tasks in YAML or Markdown with a description, acceptance criteria, and scope boundaries (which directories or modules the agent should work in). The format is simple: 'Fix the pagination bug in src/components/Pagination.tsx' or 'Add unit tests for the billing module.' Conductor takes each task definition and launches a Claude Code session with that context. The primary cost isn't the tool (Conductor itself is free) — it's the Anthropic API usage. Running 4 parallel Claude Code sessions uses roughly 4x the API tokens of a single session. Your Anthropic API tier needs to support the concurrent request rate. Start with 3-4 parallel sessions and scale up based on your rate limits and budget. Conductor is a niche tool. It's useful only if you're already a heavy Claude Code user who regularly has multiple independent tasks to parallelize. If you use Claude Code once a week for a single task, Conductor adds nothing. If you use Claude Code daily and routinely have 5+ independent tasks queued up, Conductor turns a bottleneck into a batch operation. The honest take: Conductor doesn't make Claude Code smarter or more capable. It makes it faster by removing the sequential constraint. The quality of each individual task's output is exactly what Claude Code would produce on its own. Conductor's value is pure throughput — the same quality, multiplied by the number of parallel sessions.
Install with Homebrew
brew install --cask conductorDeep Dive: Parallelizing AI Coding Work
How Conductor's approach to parallel execution fits into the broader AI-assisted development landscape.
History & Background
AI coding assistants started as autocomplete (Copilot, 2021) and evolved into autonomous agents (Claude Code, Codex, 2024-2026). The next logical step is orchestration — managing multiple agents working simultaneously. Conductor emerged from the observation that most developers' task backlogs contain many independent items that could be parallelized. A single Claude Code session is powerful but sequential. Conductor removes the sequential constraint.
How It Works
Conductor is a local orchestrator that spawns Claude Code processes. Each process runs in a separate shell with its own git worktree (a git feature that allows multiple working directories from the same repository). This provides true filesystem isolation — agents can't accidentally read or modify each other's in-progress changes. Conductor monitors process exit codes, captures stdout/stderr, and parses Claude Code's structured output to determine task success or failure.
Ecosystem & Integrations
Conductor integrates with Claude Code's CLI interface and standard git. It doesn't require any cloud services beyond the Anthropic API that Claude Code already uses. Task definitions are plain YAML or Markdown files that can be committed to your repository, shared with teammates, or generated programmatically from issue trackers via scripts.
Future Development
Future development may include integration with issue trackers (automatically create tasks from GitHub Issues), smarter conflict detection using AST analysis (understanding code dependencies, not just file paths), and support for dependent task chains (run Task B after Task A completes). The current focus is stability and compatibility with Claude Code updates.
Key Features
Parallel Claude Code Sessions
Define 3, 5, or 10 tasks and Conductor launches that many Claude Code sessions simultaneously. Each session runs independently in its own process with its own context window. Sessions don't share state or interfere with each other. The number of parallel sessions is configurable and limited primarily by your Anthropic API rate limits. Most users run 3-5 concurrent sessions — enough to clear a sprint's worth of independent tasks in a sitting.
Git Branch Isolation
Each parallel session works on its own git branch, created and named automatically by Conductor. When a session completes, you have a clean branch with only that task's changes, ready for review and merge. If a task fails or produces bad output, you discard the branch without affecting other work. This isolation is what makes parallel execution safe — agents can't corrupt each other's work because they're operating on separate branches of the same codebase.
Conflict Detection
Before launching parallel sessions, Conductor analyzes your task definitions and the codebase to identify potential file conflicts. If Task A says 'refactor the auth module' and Task B says 'update the login flow,' Conductor warns that both might modify src/auth/ and suggests running them sequentially instead. This pre-flight analysis prevents the worst-case scenario: two agents making incompatible changes to the same files, resulting in merge conflicts that take longer to resolve than doing the tasks sequentially would have.
Progress Dashboard
A terminal dashboard shows the status of all active sessions: which tasks are running, which have completed, how long each has been running, and any errors or warnings. You can drill into any session to see its current activity. The dashboard lets you monitor a batch of parallel tasks without switching between terminal windows or tailing log files manually.
Results Aggregation and Summary
When all sessions complete, Conductor generates a summary: each task's success/failure status, files modified, lines changed, test results (if tests were part of the acceptance criteria), and any issues that need manual attention. The summary gives you a single review point for all parallel work instead of checking each branch individually. You can review branches in priority order based on the summary.
Task Definition Format
Tasks are defined in YAML or Markdown with three fields: description (what to do), scope (which files/modules/directories), and acceptance criteria (how to verify completion). The format is intentionally simple — you shouldn't spend more time writing task definitions than the tasks would take manually. Example: 'description: Fix the off-by-one error in pagination. scope: src/components/Pagination.tsx, src/hooks/usePagination.ts. acceptance: All pagination tests pass, page count matches total items.'
Who Should Use Conductor?
1Solo Developer Clearing a Backlog
A solo developer has accumulated 12 GitHub issues: 6 bug fixes across different modules, 3 test coverage improvements, and 3 small feature requests. Each is independent — different files, different modules. They write task definitions for all 12, set parallelism to 4, and launch Conductor. Conductor processes them in 3 batches of 4. Within 3 hours, all 12 branches are ready for review. What would have taken 2-3 days of sequential Claude Code work is done in an afternoon.
2Tech Lead Preparing for a Demo
A tech lead needs 5 features implemented before a demo tomorrow: a search bar, a filter dropdown, an export button, a loading skeleton, and a dark mode toggle. All 5 are in different components with no shared dependencies. They define each as a Conductor task and launch all 5 in parallel. Within 90 minutes, 5 branches are ready. The tech lead reviews each branch, merges them in order, and has a working demo before lunch.
3Open Source Maintainer Tackling Issues
An open source maintainer has 8 'good first issue' bug reports that have been open for months. Each is a small, isolated fix in a different part of the codebase. They define each bug as a Conductor task with the issue description, reproduction steps, and expected behavior. Conductor launches 8 sessions. By the end of the day, 8 pull requests are ready, each with the bug fix, updated tests, and a clean commit message. The maintainer reviews and merges them, clearing the backlog in one push.
How to Install Conductor on Mac
Conductor requires Claude Code and an Anthropic API key. Install both before setting up Conductor.
Install Prerequisites
Ensure Claude Code is installed: brew install claude-code. Configure your Anthropic API key: export ANTHROPIC_API_KEY=your-key-here (add to ~/.zshrc for persistence).
Install Conductor
Run: brew install --cask conductor. This installs the Conductor macOS app (version 0.51.1).
Verify Setup
Run: conductor --check. This verifies that Claude Code is accessible, your API key is valid, and your git configuration is correct. Fix any issues before running parallel sessions.
Create Your First Task File
Create a tasks.yaml file with 2-3 simple tasks. Run: conductor run tasks.yaml --parallel 2. Watch the dashboard as two Claude Code sessions work simultaneously. Review the resulting branches.
Pro Tips
- • Start with 2-3 parallel sessions to learn the workflow before scaling up.
- • Write task definitions with explicit scope boundaries (file paths, module names) to minimize conflict risk.
- • Monitor your Anthropic API usage dashboard alongside Conductor to avoid hitting rate limits.
- • Use the --dry-run flag to see which branches Conductor would create and which conflicts it detects, without actually launching sessions.
Configuration Tips
Set Parallelism Based on API Tier
Your maximum parallel sessions should match your Anthropic API rate limits. Free tier: 1-2 sessions. Standard tier: 3-5 sessions. Scale tier: 5-10 sessions. Running more sessions than your rate limit allows causes sessions to queue and timeout.
Scope Tasks to Separate Directories
The best Conductor results come from tasks that touch completely different parts of the codebase. 'Fix bug in auth module' and 'Add tests for billing module' is ideal — different directories, no overlap. 'Refactor user service' and 'Update user API' is risky — both touch user-related code. Scope tasks explicitly to avoid hidden overlaps.
Use Acceptance Criteria for Quality
Include specific acceptance criteria in each task: 'All existing tests pass,' 'New unit tests cover the fix,' 'No TypeScript errors.' Claude Code checks these criteria before completing the task. Without criteria, the agent might fix the surface problem without verifying correctness.
Review Branches Before Merging
Conductor creates branches, not merged code. Review each branch as you would a pull request: check the diff, run tests, verify the acceptance criteria are met. Conductor accelerates the work; you still own the quality gate.
Alternatives to Conductor
Conductor is purpose-built for parallelizing Claude Code. Alternatives offer different approaches to scaling AI-assisted development.
Claude Code (Solo)
Claude Code alone handles one task at a time with the same quality. Conductor adds parallelism — same quality, more throughput. Use solo Claude Code for complex, multi-step tasks that require deep context. Use Conductor for batches of independent, smaller tasks.
Codex (OpenAI)
OpenAI's Codex runs autonomous agents in cloud sandboxes with built-in parallelism and PR creation. Conductor runs locally using Claude Code, giving you more control over the execution environment and lower latency. Codex is a fully hosted solution; Conductor is a local orchestrator.
Custom Shell Scripting
You could script multiple Claude Code sessions with bash — spawn processes, manage branches, collect output. Conductor adds conflict detection, progress monitoring, results aggregation, and branch management. It's the difference between building infrastructure and using it.
Pricing
Conductor itself is free — no license, no subscription. The cost is Anthropic API usage: running N parallel sessions uses approximately N times the API tokens of a single session. A 4-session batch of moderate tasks might cost $5-15 in API usage depending on task complexity. Budget based on your typical Claude Code usage multiplied by the number of parallel sessions.
Pros
- ✓Multiplies Claude Code throughput through parallel execution
- ✓Git branch isolation prevents agents from interfering with each other
- ✓Conflict detection catches overlapping task scopes before launch
- ✓Free tool — cost is only the Anthropic API usage you'd spend anyway (faster)
- ✓Simple YAML/Markdown task definition format
- ✓Progress dashboard monitors all sessions from one view
- ✓Results aggregation provides a single review point for all parallel work
Cons
- ✗Only useful for heavy Claude Code users with multiple independent tasks
- ✗API costs scale linearly — 4x parallel means 4x API spending
- ✗Requires tasks to be truly independent (no shared file modifications)
- ✗Anthropic API rate limits cap the maximum useful parallelism
- ✗Doesn't improve individual task quality — only throughput
- ✗Niche tool with a small user base compared to general-purpose AI coding tools
Community & Support
Conductor has a focused community of Claude Code power users who share task templates, configuration patterns, and workflow tips. The GitHub repository is the primary support channel, with issues and discussions. A Discord channel provides real-time help for setup and troubleshooting. The community is small but dedicated — most users are professional developers who adopted Conductor to handle the volume of AI-assisted tasks in their daily workflow.
Frequently Asked Questions about Conductor
Our Verdict
Conductor is a force multiplier for developers who use Claude Code heavily. It takes the sequential bottleneck of one-task-at-a-time AI coding and turns it into parallel batch processing. The git branch isolation and conflict detection make parallel execution safe. The task definition format is simple enough to learn in minutes. The catch: you need to be a heavy Claude Code user with multiple independent tasks regularly, and your API budget needs to support the parallelism. For its target audience — professional developers doing 5+ AI-assisted tasks per day — Conductor compresses a day of work into a few hours.
About the Author
Related Technologies & Concepts
Related Topics
AI Coding Agents
Tools that automate coding tasks through autonomous AI agents.
Sources & References
Fact-CheckedLast verified: Feb 23, 2026
Key Verified Facts
- Defines Claude Code as a single autonomous AI coding agent that developers can delegate terminal-based engineering tasks to.[cite-1]
- Explains how Conductor acts as a project manager to spin up multiple Claude Code instances simultaneously to eliminate sequential bottlenecking.[cite-2]
- Details how Conductor automatically isolates tasks by assigning each Claude Code worker its own Git branch and managing the eventual merges.[cite-3]
- Outlines the concurrent API request limits and token quotas developers must account for when running parallel Claude Code sessions via Conductor.[cite-4]
- The official open-source repository for the Conductor command-line tool, showing the implementation of parallel task delegation.[cite-5]
- 1Claude Code Overview - Anthropic Documentation
Accessed Mar 1, 2026
"Defines Claude Code as a single autonomous AI coding agent that developers can delegate terminal-based engineering tasks to."
- 2Parallel Execution - Conductor Documentation
Accessed Mar 1, 2026
"Explains how Conductor acts as a project manager to spin up multiple Claude Code instances simultaneously to eliminate sequential bottlenecking."
- 3Git Branch Management with AI Workers - Conductor Docs
Accessed Mar 1, 2026
"Details how Conductor automatically isolates tasks by assigning each Claude Code worker its own Git branch and managing the eventual merges."
- 4Anthropic API Rate Limits
Accessed Mar 1, 2026
"Outlines the concurrent API request limits and token quotas developers must account for when running parallel Claude Code sessions via Conductor."
- 5Conductor - Y Combinator
Accessed May 6, 2026
"Founded in 2024 by Jackson de Campos and Charlie Holtz, Conductor is a YC-backed company with 6 employees based in San Francisco. The company raised a $22m Series A."
- 6conductor — Homebrew Formulae
Accessed May 6, 2026
"Homebrew Cask formula for Conductor. Current version: 0.51.1. Analytics show 3,777 installs in the past year, 2,176 in the last 90 days, and 698 in the last 30 days."
- 7Conductor wants to be the project manager for your AI coding agents
Accessed Mar 1, 2026
"Discusses how Conductor solves the sequential bottleneck of standard AI coding tools by allowing developers to run multiple autonomous agents simultaneously."
- 8Orchestrating AI developers: A look at Conductor for Claude Code
Accessed Mar 1, 2026
"Reviews Conductor's ability to assign independent tasks to separate instances and seamlessly collect the results into a unified codebase."
- 9SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
Accessed Mar 1, 2026
"Provides the baseline benchmark metrics for autonomous coding agents, demonstrating the base capability of a single Claude Code instance before parallelization."
- 10Benchmarking Parallel Claude Agents - Conductor Blog
Accessed Mar 1, 2026
"Publishes benchmark results showing a 4x reduction in total task completion time when using Conductor to parallelize 5 independent feature requests."
Research queries: Conductor Claude Code parallel sessions AI coding 2026