We ditched worktrees for Claude Code. Here's what we use instead
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| Source: Dev.to | Original article
A team of engineers at a Nordic AI consultancy announced that they have abandoned the conventional git‑worktree trick for juggling multiple Claude Code agents and are now relying on Claude Code’s own “worktree” flag together with lightweight project clones.
The shift came after weeks of wrestling with the classic workflow: developers would spin up a fresh git worktree for each agent, run a full npm install, rebuild Docker‑Compose stacks and then fight occasional merge conflicts when two sessions edited the same file. “Bootstrapping each worktree was a hidden cost,” one engineer explained, “and the shared port space in our Docker environment made the approach brittle.”
Claude Code, Anthropic’s code‑generation platform, introduced a built‑in `--worktree` option that creates an isolated copy of the repository, checks out a fresh branch, and scopes the AI session to that snapshot. The new process eliminates the need for separate git worktrees, sidesteps merge‑conflict headaches and lets the team launch dozens of agents in parallel with a single command. The workflow also leverages Claude Code’s session picker and permission modes, allowing each agent to store its own instructions and memory without contaminating others.
Why it matters is twofold. First, it cuts developer overhead dramatically, freeing time that was previously spent on environment setup and conflict resolution. Second, it showcases a growing trend where AI‑assisted development tools provide native project isolation, reducing reliance on traditional version‑control hacks. As more teams adopt Claude Code for large‑scale code generation, the built‑in worktree feature could become a de‑facto standard for parallel AI‑driven coding.
Watch for Anthropic’s next update, which is expected to extend the worktree flag with container‑level isolation and tighter CI/CD hooks. If the feature proves stable, other LLM‑powered IDEs may follow suit, reshaping how developers orchestrate multiple AI agents in a single codebase.
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