Launch HN: Freestyle – Sandboxes for Coding Agents
137 points - today at 4:32 PM
We’re Ben and Jacob, cofounders of Freestyle (https://freestyle.sh). We’re building a cloud for Coding Agents.
For the first generation of agents it looked like workflows with minimal tools. 2 years ago we published a package to let AI work in SQL, at that time GPT-4 could write simple scripts. Soon after the first AI App Builders started using AI to make whole websites; we supported that with a serverless deploy system.
But the current generation is going much further, instead of minimal tools and basic serverless apps AI can utilize the full power of a computer (“sandbox”). We’re building sandboxes that are interchangeable with EC2s from your agents perspective, with bonus features:
1. We’ve figured out how to fork a sandbox horizontally without more than a 400ms pause in it. That's not forking the filesystem, we mean forking the whole memory of it. If you’re half way down a browser page with animations running, they’ll be in the same place in all the forks. If you’re running a minecraft server every block and player will be in the same place on the forks. If you’re running a local environment and an error comes up in process that error will be there in all the forks. This works for snapshotting as well, you can save your place and come back weeks later.
2. Our sandboxes start in ~500ms.
Demo: https://www.loom.com/share/8b3d294d515442f296aecde1f42f5524
Compared with other sandboxes, our goal is to be the most powerful. We support full Linux + hardware-virtualization, eBPF, Fuse, etc. We run full Debian with multiple users and we use a systemd init instead of runc. Whatever your AI expects to work on debian should work on these vms, and if it doesn’t send a bug report.
In order to make this possible, we’ve moved to our own bare metal racks. Early in our testing we realized that moving VMs across cloud nodes would not have acceptable performance properties. We asked Google Cloud and AWS for a quote on their bare metal nodes and found that the monthly cost was equivalent to the total cost of the hardware so we did that.
Our goal is to build the necessary infrastructure to replicate the human devloop on the massively multi-tenant scale of AI, so these VMs should be as powerful as the ones you’re used to, while also being available to provision in seconds.
Comments
If so, we'd very much like to test this. We make extensive use of Claude Code web but it can't effectively test our product inside the sandbox without running a K8s cluster
When I’m thinking of sandboxes, I’m thinking of isolated execution environments.
What does forking sandboxes bring me? What do your sandboxes in general bring me?
Please take this in the best possible way: I’m missing a use case example that’s not abstract and/or small. What’s the end goal here(
The cost argument for owning the hardware for this specific use case also makes sense, considering the scale these agent environments will demand. Also worth noting, sandboxes are effectively an open attack surface; architecting them not to be in your main VPC is a sound security decision from the start.
If the machine can fork itself, it could allow for some really neat auto-forking workflows where you fuzz the UI testing of a website by forking at every decision point. I forget the name of the recent model that used only video as its latent space to control computers and cars, but they had an impressive demo where they fuzzed a bank interface by doing this, and it ended up with an impressive number of permutations of reachable UI states.
We ended up creating localsandbox [0] with that in mind by using AgentFS for filesystem snapshotting, but our solution is meant for a different use case than Freestyle - simpler FS + code execution for agents all done locally. Since we're not running a full OS it's much less capable but also simpler for lots of use cases where we want the agent execution to happen locally.
The ability to fork is really interesting - the main use case I could imagine is for conversations that the user forks or parallel sub-agents. Have you seen other use cases?
The memory forking seems like a cool technical achievement, but I don't understand how it benefits me as a user. If I'm delegating the whole thing to the AI anyway, I care more about deterministic builds so that the AI can tackle the problem.
> we mean forking the whole memory of it
How does this work? Are you copying the entire snapshot, or is this something fancy like copy-on-write memory? If it's the former, doesn't the fork time depend on the size of the machine?Congrats on the launch. This is cool tech
We're working on a similar solution at UnixShells.com [1]. We built a VMM that forks, and boots, in < 20ms and is live, serving customers! We have a lot of great tools available, via MIT, on our github repo [2] as well!
> Freestyle is the only sandbox provider with built-in multi-tenant git hosting — create thousands of repos via API and pair them directly with sandboxes for seamless code management. On top of that, Freestyle VMs are full Linux virtual machines with nested virtualization, systemd, and a complete networking stack, not containers.
It makes me think of the git automation around rigs in Gas Town: https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...
Edit: I realize the Loom is a way to look at it. Loom interrupted me twice and I almost skipped it. However it gave me a better idea of what it does, it "invents" snapshotting and restoring of VMs in a way that appears faster. That actually makes sense and I know it isn't that hard to do with how VMs work and that it greatly benefits from having only part of the VM writable and having little memory used (maybe it has read-only memory too?).