Conductor moves parallel AI coding agents to the cloud with Vercel Sandbox

Conductor, a six-person startup, hit a problem familiar to many people who build developer tools: how to scale compute without being tied to local hardware. Its tool for managing a fleet of AI coding agents needed a cloud layer. The team chose Vercel Sandbox, and developers can now run several agents in parallel and close their laptops.

The problem with local execution

Conductor started as an app that a developer ran on their own laptop. With one or two agents it worked well: intuitive and fast. But when teams wanted to scale up, running more agents and giving them more time to work on different branches in parallel, the problems began. The fan ran at full blast, the processor overheated and the battery drained in twenty minutes. Worst of all, closing the laptop lid stopped the agents completely.

Engineers at Notion and Linear, early Conductor users, quickly felt these limits. They saw the tool's potential: each agent works on a separate branch of the codebase, and all of them can run at once. But they could not leave a laptop running all day. Demand for cloud execution arrived fast and loud.

The cloud solves it

The solution is called Cloud Workspaces, and it is built on Vercel Sandbox. The idea is simple: when a developer opens a new workspace, the agents no longer start on their machine but on a remote server in the cloud. The laptop can be switched off. The interface is unchanged, and to the user it looks identical to the local version.

Users don't see a difference between the local and cloud versions.

They just open a workspace the way they always have and work. It's magic, because Vercel Sandbox is very fast.

The workflow now looks like this:

• Open several workspaces with agents on different codebase branches in parallel
• Close the laptop and go to a meeting or head home
• Come back two hours later and see what the agents did
• Discuss with the team which changes to merge into the main branch and which to redo

Why Vercel

For a young startup, moving from a local setup to the cloud is a big decision. The first users work at large companies: Linear, Ramp, Notion. They want to know who is trusted with their code and data. This is not just a technical choice of provider; it is a conversation about long-term reliability.

Conductor evaluated several sandbox providers against these criteria: cold-start speed, support for snapshots, long-term reliability, quality of technical support and developer experience for its own team. Vercel won on every count. Charlie Holtz, Conductor's CEO, previously worked at Vercel, so he knows the company well: "There are so many cloud sandbox providers on the market. We needed one that is fast and reliable and can give us serious technical support. Vercel checked all those boxes and gave us a genuinely good developer experience."

Model agnosticism

Conductor deliberately did not tie itself to a single model or framework. It currently supports Claude Code, Codex and other coding agents. This is a strategic choice for the future: something new happens in AI every three months, while Conductor's cloud layer stays universal. If a perfect new coding tool appears tomorrow, Conductor can add it without rebuilding its whole infrastructure.

What this means

Parallel AI agents are finally moving from the lab into production cloud. This is no longer an idea from a conference talk; it is a real tool that engineers at Notion, Linear, Ramp and Life360 use every day. For developers it means one thing: you can rest easy. Your agents will keep working while you drink coffee, go to a meeting or take a day off. Local hardware no longer limits the scale of the work.