Mac mini vs. boxes.dev for coding agents

Running your coding agents on a Mac mini is a popular setup. You can leave that machine on a desk, install your tools, and start parallel Claude Code and Codex sessions there without them touching your laptop. And with remote control, you can reach the same agent sessions from your phone. It's a convenient way to work.

You can do something similar for your team: buy a Mac mini for every engineer, or share a larger server. You can even just put a few spare laptops to work as a small cluster.

The question is, how much do you still have to manage once the computers are running?

Boxes.dev solves the same problem as a Mac mini: moving work off your laptop. Each independent task gets its own cloud devbox, with your development environment and its own resources. You can let agents work in parallel without setting up worktrees or deciding which computer has room for the next one.

What a second computer solves

Moving an agent off your laptop has an immediate benefit: closing your laptop no longer pauses the computer doing the work. A long build can continue while you leave the office, provided the host stays awake and the process keeps running after you disconnect.

The basic tools are well established. macOS includes Remote Login over SSH, and tmux keeps terminal programs running when you detach. An SSH client or a remote interface for your agent can make the work reachable from another computer or a phone.

For one engineer with a spare computer and a few tasks, that may be plenty. You know where the work is, you've already installed the dependencies, and keeping the computer available isn't much trouble.

For a team, there are several ways to arrange the hardware, each with a different set of tradeoffs.

A Mac mini for every engineer

Giving everyone a Mac mini makes ownership clear. Each engineer has a host, controls its environment, and can run agents without using their laptop's resources. One person's build won't use another person's Mac.

Within that Mac, though, the tasks still share the same resources. An engineer running six agents may have six worktrees, several dev servers, and multiple test suites competing for its memory and CPU. A larger configuration raises the ceiling, but the work still has to fit.

Worktrees keep the agents' code changes separate, but their apps will still need to run side by side. You'll have to coordinate ports and local databases so that one agent can test its changes without interfering with another.

Capacity can also be uneven across the team. One engineer's Mac may sit idle while another's is full. Borrowing the idle one means arranging access and preparing the project there. That can be straightforward, but someone has to do it, and now the engineer's work is spread across two hosts.

Each Mac also needs updates, credentials, disk cleanup, and a way to recover useful work if it fails. These are familiar responsibilities, but they add up when every engineer owns a second development computer.

One shared Mac mini or a larger server

A shared server puts the capacity in one place. Engineers can use it as needed, and the team has fewer computers to maintain. With enough memory, storage, and CPU, it can run many tasks comfortably.

The tradeoff is that more people depend on the same host. Several builds starting together can slow one another down. A full disk can interrupt everyone using it. Maintenance has to account for other people's unfinished work.

Separate user accounts and worktrees help organize files and access. They don't give each task its own pool of hardware resources. The same is true of containers: Docker supports memory and CPU limits, but those limits divide the capacity the host already has. Setting them is useful; deciding how to divide a busy server is still your team's job.

The same port and database coordination now extends across the team. An agent testing a migration could change the local database another engineer is using, or two copies of the app could try to bind the same port. Everyone using the server will need to follow the same conventions for keeping their environments separate.

A pool of spare laptops

Reusing laptops can be an inexpensive way to try this, particularly if the team already owns them. Assign an agent to an available computer and keep it plugged in and reachable.

Over time, you need a way to track which laptop has which project, whether it's available, and whether it has the right tools. Different hardware and operating systems may need different setup. Sleep settings, updates, and network access all matter when someone expects an agent to keep working overnight.

An available laptop also isn't necessarily ready for the task you want to start. It may need a repository, credentials, dependencies, and test data before the agent can do anything useful. Scripts can make that setup repeatable. Someone still has to maintain them and decide where the next task should run.

Remote access still leaves you managing the hosts

Being able to reply from your phone is useful in all three setups. It doesn't change where the code, dev server, or database runs. If you started the task on the shared Mac, that Mac still has to be available when the agent needs to build or test.

The worktree resource problem follows the work, too. Moving ten checkouts from your laptop to a server clears space on your laptop. The server then holds the dependencies, build output, and local services for those ten tasks. A bigger server buys headroom, but every additional task uses some of it.

You can build more automation around this. A team could create a VM for each task, prepare reusable images, assign work to available hosts, and provide a common interface for finding it all. You'll then be operating a development platform, including adding capacity when the hardware fills up.

How the workflow changes on boxes.dev

With boxes.dev, you can leave agents building and testing your app in the cloud and close your laptop, just as you would with an agent on a Mac mini. The difference shows up when you want to start more work: each independent task gets its own devbox by default.

If Claude Code is working on a feature while Codex investigates a bug, each can run a separate copy of the app using the same port numbers. Each devbox can also run its own local database, so testing a migration in one won't change the other's data. You won't need worktrees to keep their code apart or a different set of ports for every task.

Each devbox has its own disk space, CPU, and memory, so starting another agent won't add another build or test suite to the same busy computer. You can keep an unfinished task around without clearing its files to make room for the next one. The new devbox will start from your project's saved development environment, without needing a spare Mac or another round of setup. Your team can share that starting environment, too. See how boxes.dev works.

You can open the app an agent is running, test its changes, and review the code from your laptop. If you need to leave, the mobile app opens the same threads, so you can answer a question or ask for another change from your phone. You won't need to remember which computer has the task or reconnect to the right terminal; the conversation and its devbox will stay together.

The main differences look like this:

Devboxes still have resource limits, and your plan determines how many can be awake at once. You'll also need to keep your app's saved environment up to date as its requirements change. Boxes.dev handles the computers underneath it, including finding capacity for each devbox, so adding another task won't mean buying and maintaining another computer.

When keeping your own hardware makes sense

If you already own suitable hardware, have steady workloads, and are happy maintaining it, a DIY setup can be economical. Include the time spent on setup, access, upgrades, and recovery in the comparison, alongside the purchase price and ongoing costs. There isn't one break-even number that fits every team.

The appeal of boxes.dev is being able to stop thinking about the computers. You can leave one task ready for review and start the next without deciding which host to use or which worktree to clear out first.

Set up a project, get your app running, and try a few independent tasks. Your laptop can be open, closed, or left at home; you'll come back to the same work without keeping track of a collection of computers behind it.