Hi Product Hunt!
I m Lili, one of the Engineers at Warp who built Oz an orchestration platform for cloud agents.
Oz helps devs run coding agents at scale safely with orchestration, observability, a unified local <> cloud experience.
I worked on setting up our cloud environments with all the tools agents need to run code (there is a lot to unpack here, getting cloud agents to work on arbitrary base docker images was more challenging than you might think!), surfacing agent runs and artifacts like PRs and plans in our desktop and web apps, and integrating the Oz agent directly into GitHub actions.
Building with and on top of Oz has been so much fun. The platform is incredibly flexible, and the primitives we ve built unlock a whole new level of experimentation and automation.
AMA about how we built Oz, our favorite use cases, and where we see the platform going!
Warp
Hey Product Hunt 👋
Zach here - Founder and CEO at Warp. Our team is excited to launch Oz, the orchestration platform for cloud agents.
Oz makes it easy to scale up to hundreds of cloud agents, keep tasks running when you step away from your laptop, and turn agent skills into agent automations.
Why we built Oz and what it does
Developers today are running 3-5 local agents to fix bugs but once you try to go beyond that, things start to break down: your laptop hits capacity, you can’t see what your agents are doing, and agents start to be more trouble than they’re worth.
Deploy agents from anywhere: From the Warp desktop app, on the web, your phone, using Warp’s SDK, or even the CLI.
Isolated cloud environments: Set up isolated cloud environments for agents to run that can index as many GitHub repositories as you want.
Build apps on top of agents. Use CLI and API access to build bug triage systems, incident response tools, or any app that needs an agent backend.
If you're looking for a starting point, try automating something small - a recurring task that's tedious but straightforward and watch your productivity compound.
We can’t wait to see what you build and I’d be curious to hear the community’s thoughts on whether they think cloud agents are going to be the future?
Feel free to comment any questions/feedback you have below and one of our engineers will respond. ✌️
Migma AI
been a Warp fan since early beta — Oz looks like a massive step up for agent orchestration. 🪄 the parallel cloud execution is a game changer for long-running dev tasks. what's the most common automation you've seen devs build on top of Oz so far? 🚀
Warp
Thanks for the kind words @adam_lab 🙌
We've seen so many great things built on top of Oz, but some of the most common ones that people are starting with are around automating simple but time-consuming chores: auto-updating docs, triaging GitHub issues, running reports on a schedule. These are well-defined & understood problems that you can easily hand off to an agent to do on it's own.
And then the cool stuff is starting to show as well... OpenClaw alternatives, agents talking to each other to get stuff done, orchestrating third-party agents, and a bunch of others. Super excited to see what everyone is building and creating.
@adam_lab @petradonka You have my attention at "OpenClaw alternatives." I have a major project on which I'd like to develop and deploy some AI agents, but I have had no idea how to get started. I've been looking at OpenClaw but hesitant to pull the trigger. It just seems like overkill and a security risk.
@adam_lab @jay_bienvenu might want to take a look at https://moltbookagents.net which has a simple setup guide plus a guide to securing the agent in a self-contained NAS. Might be a quick solution
Warp
Cloud agents feel inevitable. Curious how you balance flexibility with guardrails so things don’t spiral in production.
Warp
Super proud of the team for rethinking how we start, drive, and finish tasks with agents from first principles. Warp built the right core abstractions early on, and it's paying off! Oz to the 🌙
Product Hunt
Congrats on the launch! Moving agents to isolated cloud environments makes sense once local setups hit limits. How do you handle coordination and state management across hundreds of agents so tasks don’t conflict, duplicate work, or drift from the original objective when running asynchronously?
The `shell` code is not working.