Agent teams in Codex and when the extra agents pay off

The rule that predicts success

Running agent teams in Codex works when the subtasks do not need to agree with each other. If two agents must converge on the same interface, the same data shape, or the same naming, you have created a coordination problem that used to be one agent's internal state. Coordination between agents is expensive and unreliable in a way coordination inside one session is not.

So the question to ask before splitting: Could two engineers do these pieces independently once the interface is agreed? If yes, split. If they would need a fifteen minute conversation first, do not.

What splits cleanly

• Mechanical migrations across many files. Renaming a deprecated call, updating an import path, moving forty test files to a new assertion style.
• Independent bug fixes in unrelated modules.
• One agent writing code and a separate one reviewing it afterwards, which is really a pipeline rather than a team.
• Research fan-out. Several agents reading different parts of a large codebase and reporting back, with no edits at all.

That last one is underused. Read-only agents avoid edit conflicts, although their data access and token cost still need boundaries, and answering "where is this concept implemented" across a monorepo is exactly the job where parallelism wins with no merge risk.

What does not split

A new feature that touches the API, the database, and the frontend. People try this constantly. Three agents, three layers, sounds tidy. What comes back is an endpoint returning snake_case, a client expecting camelCase, and a migration that added a nullable column the API assumes is populated. Each piece is individually defensible. Together they do not run.

The fix, when a team insists on trying, is to have one agent define the contract first and write it to a file, then let the others work against that file. That can work when each agent receives the same versioned contract and an integration check verifies their combined output. The coordination cost may outweigh the benefit for a small feature.

The operational cost nobody budgets for

Agents editing overlapping files need isolation or an explicit serial handoff. Separate worktrees can isolate edits; read-only tasks or deliberately serialized edits do not require a worktree per agent.

Then you have three branches to merge, three diffs to review, and no single place where the whole change is visible. Review is the bottleneck, and parallel agents make more of the thing that was already your bottleneck. Track the number of accepted, reviewed changes and the integration work they require, rather than counting generated pull requests alone.

For a concrete trial, write one JSON response example and its required fields before splitting an API and client task. Have both agents use that fixture, then run the client against the actual API response. A passing fixture test alone is insufficient if the deployed response has different field names or nullability.