Parallel coding agents need boundaries before speed

Several coding agents can work at once. They should not share a branch, a database, or an undefined idea of done. Parallelism needs ownership and a merge point.

The next software-industry trend after one coding agent is several of them running at once. GitHub is showing parallel agent sessions as a practical workflow, and the attraction is obvious: one agent checks a migration, another writes tests, and a third reviews the API. More hands should mean less waiting. In a real repository, more hands can also mean three people moving the same chair.

Parallelism is useful only when the work is actually separable. I would not put three agents on OnMission’s assignment flow and hope Git resolves the product decisions. I would give one agent the schema, one the focused tests, and a human the merge decision. The agents can move in parallel. The contract cannot be ambiguous in parallel.

Parallel agents reduce waiting only when they do not share an undefined decision.

Ayush Adhikari

Step 1: Split the outcome into owned slices

Do not assign “build the feature” to three agents. Split the work by ownership and proof. One agent can define the data shape, another can add tests around the current contract, and a third can document the migration. If two agents must decide the same invariant, they are not independent tasks yet.

Step 2: Isolate each agent’s checkout

A shared working tree makes the agent’s context lie. It may read files another agent has half-edited, run tests against an uncommitted change, or overwrite a useful fix. Use a branch or worktree per task. The merge point should be boring enough that a human can see which idea won.

Step 3: Keep databases and external effects separate

Two agents can have isolated files and still corrupt the same environment. Do not let an experimental agent send real email, create live Stripe objects, run a destructive migration, or deploy a preview over another agent’s preview. Give each workflow test data, fake providers, a unique port, and approval for side effects.

• Use separate test data or schemas for database-writing tasks.
• Use provider test mode and deterministic fixtures for payments and email.
• Give preview deployments a branch-specific name and URL.
• Require human approval for migrations, deploys, and externally visible actions.

Step 4: Validate each slice before the merge queue

A green full build at the end can hide which agent introduced the failure. Every agent should leave a small proof: the focused test, the typecheck, the migration dry run, or the rendered page. Then the merge step can investigate one failure instead of asking three agents to explain a red pipeline.

Parallel does not mean unsupervised Agents can prepare alternatives, test assumptions, and produce diffs. One person should decide which contract enters the main branch.

Step 5: Merge one decision at a time

Merge the change that establishes the contract first. Then rerun the other slices against it. Do not solve conflicts by taking the newest text from whichever agent finished last. A merge conflict is often a product decision wearing Git’s clothing.

• Copy: one owner per decision, one branch or worktree per agent, and a focused proof from every slice.
• Copy: parallel research and tests before parallel writes to the same contract.
• Do not copy: three agents editing the same service because the task is “small.”
• Do not copy: shared credentials, shared test data, or a shared deployment target.

Several agents can be a useful team. They are not a substitute for architecture. Split the work, isolate the state, collect evidence, and keep one human merge decision. That is how parallelism becomes delivery instead of a faster way to manufacture a confusing diff.

Parallel coding agent questions

What is the main risk of running coding agents in parallel?

The risk is that agents edit the same surface, make incompatible assumptions, or share state that makes results hard to reproduce. Isolation and explicit ownership reduce that risk.

Should parallel agents share one branch?

Usually no. Give each meaningful task its own branch or worktree, then merge through one review point. Shared branches turn independent work into an untracked race.

How many coding agents should run at once?

As many as the validation and review capacity can handle. Start with two small, independent tasks. More agents are not faster when review and integration are the bottleneck.