Hey Nathan! I remember Rivet from Playflow, back when you guys did game server orchestration. Great to see you guys grow!
Have you had agents like claude code , codex etc all fully running in agent-os? Trying to understand the use case a bit better here. For context, I've recently built our own pipeline which spins up ephemeral linux vms for claude code, codex, etc which do their work & the state always persists but frees up resources when finished. Is the idea pretty much similar for agent-os here?
Also with the s3 backing changes, it reminds me a lot of the work done on celld, good to see more self-hostable durable objects out there.
Rivet is very cool. Switched a Cloudflare Durable Object piece of our infrastructure that lived in its own little fairy tale land to our own infra within the rest of our VPC. Was a very pleasant experience.
Haven't had the chance to try Rivet v3 yet but hoping to get to it soon.
Wouldn't an agent in any capacity need a sandbox runtime to do agentic work? When you say "sandboxes are too slow" do you mean needing to boot the sandbox to get back Agent state? Is the idea that state/memory/context and runtime env are separate concepts in rivet?
(I'm a professional developer but don't do any orchestration so trying to understand from basic mental model pov)
There is a notion right now of decoupling the agent loop from the sandbox, so the sandbox isn't waiting for request-response from the agent. This would probably be 90+% of all the agent work.
If you combine this with products like Sprites from Fly.io (or OSS version - agent substrate), where you pay only per execution request in a sandbox, you can have huge savings compare to the event loop inside the sanbdox. You will be billed only for request executions (tens of milliseconds per read/write, hundreds of milliseconds per search, etc.) and zero for all the waiting time during the the inference phase.
Also, if you don't require a real Linux sandbox — you might actually emulate the environment, e.g. just-bash idea with linux-like environment to give agents something that looks like their native habitat, but under the hood, it can be just CF Durable Objects SQLite or whatever else.
Probably(?) almost all knowledge work doesn't require a Linux sandbox. You can just build a document reading and editing agent that does tool calls and connects to other products via MCPs, APIs, etc. And lightweight actors make a lot of sense to me in these cases.
> Wouldn't an agent in any capacity need a sandbox runtime to do agentic work?
Developers on Rivet use 3 different patterns:
- Just agents: many agents just need tools, such as customer support or personal agents
- Agents with lightweight sandbox: Rivet provides a V8 / WebAssembly sandboxing library for running JS & Python with a filesystem, which covers most workloads like data analysis, file processing, evals, and code mode (https://rivet.dev/agentos/)
- Agent outside of the sandbox: expose the sandbox to the agent as tools, which is better for blast radius, trust boundary, and orchestration (see below)
> Is the idea that state/memory/context and runtime env are separate concepts in rivet?
Exactly, Rivet Actors support running the harness outside of the sandbox. It's often referred to "separation of head from the hands."
> When you say "sandboxes are too slow" do you mean needing to boot the sandbox to get back Agent state?
Specifically coldstarts. As LLMs are getting faster and have more realtime use cases, sandboxes are become the bottleneck on time to interactive for an agent.
My first reaction: this is weird; agentic workloads have many problems but orchestration speed ain't one of them. You spend most of the time waiting for the model! Is this for small models?
What if I just want self-hostable TypeScript actors _without agents_? I'm a long-time fan of Akka et. al., but to my knowledge Node never got a proper framework.
Hey! Rivet is pure actors at its core, there's nothing inherently specific to agents.
Instead, we provide an optional agent library that runs Pi Durable on top of actors (https://rivet.dev/agents/docs/quickstart/) or you can write your agent from scratch if you choose.
Interesting idea, horrible ux atm though, my codex/claude whatever is just as confused as me what and how are we supposed to use it exactly and all the edge cases. Hope you folks can figure out some interesting ideas to improve it though.
Hey! Can you share a bit more about what your agent is saying so we can fix this? Would love to chat with you in Discord too: https://rivet.dev/discord
Have you had agents like claude code , codex etc all fully running in agent-os? Trying to understand the use case a bit better here. For context, I've recently built our own pipeline which spins up ephemeral linux vms for claude code, codex, etc which do their work & the state always persists but frees up resources when finished. Is the idea pretty much similar for agent-os here?
Also with the s3 backing changes, it reminds me a lot of the work done on celld, good to see more self-hostable durable objects out there.
Haven't had the chance to try Rivet v3 yet but hoping to get to it soon.
(I'm a professional developer but don't do any orchestration so trying to understand from basic mental model pov)
If you combine this with products like Sprites from Fly.io (or OSS version - agent substrate), where you pay only per execution request in a sandbox, you can have huge savings compare to the event loop inside the sanbdox. You will be billed only for request executions (tens of milliseconds per read/write, hundreds of milliseconds per search, etc.) and zero for all the waiting time during the the inference phase.
Also, if you don't require a real Linux sandbox — you might actually emulate the environment, e.g. just-bash idea with linux-like environment to give agents something that looks like their native habitat, but under the hood, it can be just CF Durable Objects SQLite or whatever else.
Probably(?) almost all knowledge work doesn't require a Linux sandbox. You can just build a document reading and editing agent that does tool calls and connects to other products via MCPs, APIs, etc. And lightweight actors make a lot of sense to me in these cases.
> Also, if you don't require a real Linux sandbox — you might actually emulate the environment
We built agentOS for this: https://rivet.dev/agentos/
It provides Linux-compatible sandboxing using V8 / WebAssembly. Supports full POSIX filesystems, networking stacks, and process trees.
> Wouldn't an agent in any capacity need a sandbox runtime to do agentic work?
Developers on Rivet use 3 different patterns:
- Just agents: many agents just need tools, such as customer support or personal agents
- Agents with lightweight sandbox: Rivet provides a V8 / WebAssembly sandboxing library for running JS & Python with a filesystem, which covers most workloads like data analysis, file processing, evals, and code mode (https://rivet.dev/agentos/)
- Agent outside of the sandbox: expose the sandbox to the agent as tools, which is better for blast radius, trust boundary, and orchestration (see below)
> Is the idea that state/memory/context and runtime env are separate concepts in rivet?
Exactly, Rivet Actors support running the harness outside of the sandbox. It's often referred to "separation of head from the hands."
I wrote a bit about why a while back: https://rivet.dev/blog/2026-07-27-run-your-harness-outside-t...
> When you say "sandboxes are too slow" do you mean needing to boot the sandbox to get back Agent state?
Specifically coldstarts. As LLMs are getting faster and have more realtime use cases, sandboxes are become the bottleneck on time to interactive for an agent.
I would have lead with the durability aspect.
Instead, we provide an optional agent library that runs Pi Durable on top of actors (https://rivet.dev/agents/docs/quickstart/) or you can write your agent from scratch if you choose.
https://rivet.ironcladapp.com/