Path reservation and serialized merge queues for multi-agent Git worktrees

Parallel worktrees, one choke point

According to a recent post on dev.to, teams running large fleets of autonomous coding agents have discovered that Git worktrees solve only the first scaling problem. Worktrees let many agents write code at the same time without each one requiring a full clone on disk, but once generation is parallel, throughput collapses at the point where all those branches must converge back into a single canonical branch.

Three ways integration breaks

The post identifies three distinct failure modes at that boundary. The first is ordinary textual conflict: two agents editing the same configuration file or route index produce overlapping changes that Git cannot reconcile. The second is the hazard of handing those conflicts to an automated model, which tends to misread conflict markers. The third and most dangerous is what the author calls "silent semantic drift" — a merge that succeeds cleanly on the text level while breaking runtime contracts. The example given: one agent updates a function signature while a second agent's code still calls the deprecated version, and the merge goes through anyway.

Models are poor conflict resolvers

The central claim of the post is architectural rather than incidental: prompting an autonomous coding model to resolve Git conflicts is inherently unsafe. In the author's account, models in that role routinely invent resolution logic, silently drop changes committed by peer agents, or leave broken conflict markers in code that ends up in production builds. The recommended posture follows from that: systems should either stop conflicts from ever reaching the merge stage, or back every merge with rigid programmatic validation. Improvisation by the model is not an acceptable middle path.

Reserve paths before dispatch

The first half of the proposed design is pessimistic locking applied at task dispatch time. When the orchestrator hands a task to an agent, it simultaneously claims the exact file paths and dependencies that task will touch. The post illustrates this with a lock record for task-8842 assigned to agent-beta, reserving src/api/router.ts and src/models/user.ts with a lock status of acquired.

If a subsequent task needs to write to files already claimed, the orchestrator does not run it concurrently. Instead it forces serialized ordering based on dependencies. Conflicts over shared files are effectively designed out of the system in advance rather than detected and untangled later.

One merge lane, fail-closed testing

The second half governs integration itself. Agents continue writing code in parallel across their isolated worktrees, but merging into the canonical branch is strictly single-lane. When an agent finishes, the orchestrator rebases its branch onto the updated main branch, runs the automated test suite in that rebased context, and performs a fast-forward merge only if every check passes.

The decisive detail is the failure behavior. If the automated rebase hits merge conflicts, or the tests regress, the system fails closed. It does not hand the conflicted state back to the agent and hope the model guesses the conflict markers correctly. A broken or ambiguous merge simply does not proceed.

Why it matters

As agentic coding scales from a single assistant to dozens of concurrent agents, integration discipline becomes the limiting factor on throughput, not code generation itself. The technique described on dev.to is notable because it removes the language model from the loop at precisely the point where its mistakes are hardest to catch: a merge that looks clean while quietly discarding a peer agent's work. The trade-off is deliberate — some parallelism is sacrificed, since overlapping tasks are serialized and merges queue one at a time, but in exchange the canonical branch stays verifiable. For teams building agent orchestration or CI pipelines around swarms of coding agents, the pattern of dispatch-time path locks plus fail-closed rebase testing offers a concrete alternative to trusting an LLM with conflict resolution.