Lanes | The Workspace for Parallel AI Coding

Lanes is a specialized management layer for developers who want to deploy multiple AI coding agents simultaneously across different branches of a single project. Rather than relying on a single chat interface, the platform functions as a command center that orchestrates official CLI-based agents—such as Claude Code or Gemini—inside isolated git worktrees. This approach prevents agents from overwriting each other’s work or creating merge conflicts, as every task is confined to its own environment with dedicated setup and teardown scripts. The tool distinguishes itself by running agents through a real terminal interface, meaning it respects a user’s existing shell configurations, aliases, and direct subscriptions rather than acting as a middle-man API wrapper. From a central dashboard, users can monitor live shell output, track token consumption, and manage the status of several concurrent sessions. By integrating directly with issue trackers like GitHub and Linear, it converts tickets into active coding sessions that can eventually be pushed as pull requests. It provides the structural oversight necessary for teams looking to move beyond one-off AI chats toward a more automated, multi-threaded development workflow.

Key Features

  • Parallel execution of multiple AI coding agents
  • Automated git worktree creation for environment isolation
  • Orchestration of official CLI-based agents like Claude Code
  • Visual dashboard for monitoring session status and tokens
  • Integration with GitHub and Linear issue trackers
  • Local-first processing to keep code on the machine
  • Monaco-based inline diff viewer for code reviews
  • Dependency linking with automatic cycle detection

Use Cases

Use Case 1: Concurrent Feature and Bug Resolution

Problem: Developers often struggle to manage multiple AI-driven tasks simultaneously, leading to frequent branch switching and potential merge conflicts.
Solution: The platform automates the creation of isolated git worktrees for every session, allowing different AI agents to work on separate branches without interfering with each other.
Example: A developer assigns a CSS fix to one agent while another agent refactors a database schema in a separate, parallel environment.

Use Case 2: Automated Issue Triage from Project Management Tools

Problem: Manually setting up local environments for every ticket in a backlog is tedious and slows down development cycles.
Solution: It integrates with GitHub and Linear to import issues, automatically spinning up a dedicated workspace and agent for each task.
Example: Importing five high-priority bugs from Linear and dispatching them to multiple Claude Code instances to generate PRs concurrently.

Use Case 3: Leveraging Existing CLI Subscriptions

Problem: Many AI coding tools require expensive API credits, even if the user already pays for a consumer subscription like Claude Pro.
Solution: By orchestrating official CLIs in a real terminal environment, the tool allows users to utilize their standard interactive plans instead of paying for API meters.
Example: Running the official Claude Code CLI within the workspace to take advantage of an existing Anthropic subscription for complex refactoring.

Target audience: Best for: Software Engineers, Technical Leads, DevOps Specialists

Pricing: Open Source · Categories: Code Assistants, Developer Tools, Productivity

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Tags: AI, ai agent, code assistant, codebase, developer tools

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