Running Multiple Agents on One Repo Is Harder Than It Looks

Five IDEs. Three or four agents per IDE. One developer keeping track of all of them.

That's not a productivity hack. That's a coordination job.

The illusion of parallelism

You want to run multiple agents on the same codebase. One handles refactoring, another writes tests, a third tackles documentation. They should run in parallel, right?

The git workspace is the obvious coordination point. Agents need to avoid conflicting edits. But git is the easy part.

The harder problem is everything else: local databases, migrations, running servers, environment state. If one agent runs a migration and another expects the old schema, you're debugging phantom failures. If both try to spin up the same dev server, one wins and the other gets a port conflict that looks like a code bug.

"I think there are more shared resources than just the git workspace. If you're doing anything with a local database or migrations or trying to run a server, you might have the illusion of being able to run multiple things locally, but in practice you would need to be thoughtful about it."

Matt, Roo Cast S01E09

The illusion is that parallelism is free. The reality is that shared resources beyond git create implicit dependencies between agents.

The workaround that works today

One pattern that works, if you're willing to pay the coordination cost: open multiple IDEs, run separate agents in each, keep the context separation yourself.

"I have probably five IDEs open right now. In each of them I probably have three or four agents that I'm actively bouncing between in that particular repo because I do a lot of systems thinking. I'm the one keeping the context separate. I'm making sure they aren't stepping on each other."

Adam, Roo Cast S01E09

The cost is manual coordination. You become the orchestrator. You're tracking which agent is working on which branch, which one might touch the database, which one needs the server running. And at the end, you're the one rebasing.

This works. It's not elegant. It scales with your attention span, not with your compute budget.

The tradeoff

Parallel agents on one repo is a coordination problem, not a compute problem.

If your tasks are purely file-based with no shared runtime state, parallelism is straightforward. Branch per agent, merge at the end. But the moment you have a local database, a running server, or migration state, you need isolation that goes beyond git branches.

None of these is free. The question is which cost you want to pay: your attention, your infrastructure complexity, or your time.

Why this matters for your team

For a five-person team running multiple agents, the coordination overhead is invisible until it isn't. The first time two agents step on each other's migrations, you lose an hour debugging a problem that looks like a code bug but is actually a state conflict.

The pattern that might emerge: local and cloud agents becoming more analogous.

"Maybe you imagine a world where local and the cloud were a little more analogous to each other, where you can just kick things off in either direction and they run in parallel."

Matt, Roo Cast S01E09

If cloud agents run in isolated environments by default, the coordination problem shifts from "how do I keep agents from stepping on each other" to "how do I merge their outputs."

That's a rebase problem. Rebase problems are solvable.

How Roo Code handles multi-agent coordination

Roo Code addresses the parallel agent problem through intentional design choices. With BYOK (bring your own key), you control your token spend across multiple agents without platform markup getting in the way of running more agents.

The key capability is that Roo Code closes the loop: it proposes changes, runs commands and tests, and iterates based on results. This means each agent instance can validate its own work before you need to coordinate merges. When an agent can run tests and catch its own breaking changes, you spend less time debugging state conflicts caused by blind parallel execution.

For teams exploring multi-agent workflows, Roo Code's approval system lets you maintain human oversight without becoming the full-time orchestrator. You review diffs and approve commands intentionally, keeping agents from stepping on shared resources without constant manual monitoring.

The first step

Before running multiple agents in parallel, audit the shared resources in your workflow. Git is obvious. Databases, servers, and environment state are where the real conflicts hide.

If you can't isolate the runtime state, isolate the agents by running them sequentially. The slowdown is real, but the debugging time you save is worth it.