Parallel Development

The aitasks framework supports multiple developers (or multiple AI agent instances) working on different tasks simultaneously.

How Concurrency Is Managed

• Status tracking via git: When /aitask-pick starts work on a task, it sets the status to “Implementing”, records the developer’s email in assigned_to, and commits + pushes the change. This makes the assignment visible to anyone who pulls the latest state
• Atomic task locking: The atomic lock system prevents two PCs from picking the same task simultaneously. Locks are stored on a separate aitask-locks git branch using compare-and-swap semantics
• Atomic ID counter: The atomic ID counter on the aitask-ids branch ensures globally unique task numbers even when multiple PCs create tasks against the same repo
• Task data branch (optional): When enabled, task/plan files live on a separate aitask-data branch accessed via a worktree at .aitask-data/. This keeps task management commits off the main branch and allows independent sync via ./ait git push/./ait git pull

Git Worktrees for Isolation

When working on multiple tasks in parallel, use the git worktree option in /aitask-pick. This creates an isolated working directory at aiwork/<task_name>/ on a separate branch, so each task’s changes don’t interfere with each other. After implementation, the branch is merged back to main and the worktree is cleaned up.

Best Practices

• Run git pull before starting /aitask-pick to see the latest task status and assignments
• Use git worktrees when multiple developers work in parallel, or when running multiple code agent sessions on tasks that touch overlapping files
• Working on the current branch (without worktrees) is safe when you are a single developer giving work to multiple code agent sessions on tasks that don’t touch the same files

Parallel Planning

Complex tasks that need child decomposition can have their planning and decomposition phase run in parallel with any other work. Since only task and plan files are created — no source code is touched — there’s zero risk of conflicts. See Parallel Task Planning for the full workflow.

Parallel Exploration

/aitask-explore is read-only — it searches and reads code but never modifies source files. This makes it safe to run in a separate terminal tab while another agent session implements a task. Use this pattern to stay productive: explore and create new tasks while waiting for builds, tests, or ongoing implementations to complete.