The execution layer to control what AI agents can do as they run.

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If you're trying to give agents real work and control is what's stopping you, apply for early access today. Every new account starts with $50 in free credits, enough to run an agent for a month, with no credit card needed.
Today we're announcing @runta's $20M seed, led by @a16z. Software is constrained when you write it. Agents have to be constrained while they run. Runta is the execution layer that controls what AI agents can actually do.
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Pi 1.0 harness support is ready at Runta. Code-mode + native MCP is finally here:
Pi 1.0 runs on Runta today. Each agent gets its own machine: hands-on in a browser terminal, or headless over an API with live streaming, steering, and cancel. Pi never sees your real keys. Our egress layer swaps in model and credentials on the way out.
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Runta retweeted
Pi 1.0 runs on Runta today. Each agent gets its own machine: hands-on in a browser terminal, or headless over an API with live streaming, steering, and cancel. Pi never sees your real keys. Our egress layer swaps in model and credentials on the way out.
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Runta retweeted
Your agent doesn't need to escape the sandbox to leak your files. It just needs to run curl. We looked inside Grok Bot and Muse to answer one question: what happens after the injection lands? Our take: command review isn't enough. The check belongs at the exit, run by something the agent can't turn off.
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Runta retweeted
FrontierHarness v1.1 is coming. We're putting together an expert advisory group with maintainers of well-known coding-agent harnesses, plus related researchers from Stanford, Berkeley, and Caltech. A top-tier inference partner is also ready to sponsor the next eval runs. In v1.1 we'll cover more models, more harnesses, and a more representative task set. Expect an order-of-magnitude jump in both run count and tokens used, so the harness × model picture gets clearer. More soon.
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This is exactly why we built Runta: so teams can spend their time building the agent experience, not rebuilding runtimes, computer use, persistence, and execution infrastructure. Errand is what that leverage looks like: one developer, one week, and an open-source product you can try today.
One of our engineers built Errand, our open-source take on Grok Bot and Muse, and wrote up how it came together. One developer, one week. The app is ~4k lines of TS. Every agent still gets its own machine with a shell, a browser, and a filesystem that survives between tasks. He never wrote a provisioner or an event log infra. If you're about to build this layer yourself, that's what Runta is. Week one goes into your product instead of a provisioner. I'd like to hear where you're stuck, if you're in the middle of it right now.
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Runta retweeted
We made a little film for Errand. Cost us about $10. Someday errands will run themselves. Enjoy.
Grok Bot and Muse are great. We built an open-source version and called it Errand. Hand it a task, close the laptop, come back in the morning.
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Runta retweeted
Grok Bot and Muse are great. We built an open-source version and called it Errand. Hand it a task, close the laptop, come back in the morning.
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EXO harness support is ready. Self-evolve started!
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Runta retweeted
A cool thing is that you can use Runta to have exo agent play The Legend of Zelda: Link's Awakening
Replying to @guanlan
Try EXO on Runta under 2 mins with $50 free credit. runta.com/blog/introducing-e…
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A harness that rewrites itself needs somewhere scalable and safe to do it. Exo Harness now runs natively on Runta.
Exo Harness now runs natively on Runta. In FrontierHarness Eval, Exo was cheapest per completed task at $1.05. On the hardest task it hit its 51-step cap and quit at $1.46 while others kept spending. That is the harness you let rewrite itself. Exo's Executor holds no durable state, so the agent can modify it. History, artifacts, secrets and sandbox lifecycle sit in the Harness, out of reach. Runta provides a resumable environment, so the Exo Harness can self-evolve freely. Exo never holds the model API key, only a stub. Our egress gateway injects the real one at the provider. Code the agent wrote can read whatever the Executor can, and all the Executor has is a stub.
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Runta retweeted
really cool benchmark!! and amazing work @guanlan!! I was looking for a way to benchmark my own harness too and it was hard to quantify what's a good harness!! I did run the experiment with graff, and here are the results!! (would love to collab on things if you're free!)
Remarkable result for Exo, best price / performance. Exo's design philosophy is to expose the full harness code to the model for self improvement to be maximally bitter lesson aligned. Not just the prompt, but the entire running code and logs with ability to upgrade dynamically.
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BYOH (Bring your own Harness) is supported in FrontierHarness, 1 prompt to setup the whole runtime environment to eval your own harness.
Wondering where your harness would land on the FrontierHarness leaderboard? Last week the most common reply was "can I run mine on this." Now you can. Bring your harness and your own model key, and it runs on Runta under the exact conditions the leaderboard was built on: same gateway, every run a fresh restore of the same golden checkpoint, memory state included. See where your harness actually lands next to the rest of the field. Send us the run, and if it stands out we'll include it in the next official round.
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Runta retweeted
Front page of HN, 1700+ posts on X. Turns out a lot of people have been wondering what the harness layer actually costs , and whether the expensive ones are any better. The harness war is on.
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Runta retweeted
Replying to @guanlan
Great work Guanlan!
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Remarkable result for Exo, best price / performance. Exo's design philosophy is to expose the full harness code to the model for self improvement to be maximally bitter lesson aligned. Not just the prompt, but the entire running code and logs with ability to upgrade dynamically.
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Runta retweeted
My first eval project at @runta during my internship! A big takeaway from the work: harnesses matter just as much as models. Run identical tasks through different harnesses and you will see wildly different bills, pass rates, and wall-clock times.
Replying to @guanlan
v1.0 focused on software engineering and terminal tasks. Next we will test the full harness × model grid. Much of what we observed points to harness-model fit rather than harness quality, and we want to identify which combinations maximize pass rates while minimizing cost. Leaderboard and the long version: frontierharness.org/
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Runta retweeted
A year ago the question was which model. Now it's which harness. Pi, Exo, Claude Code, Codex, DeepSeek Harness and 4 others. Same model, same tasks, same runtime. 360 runs, 2 billion tokens. Pass rates: 50% to 67%. Cost per pass: $1.05 to $18.34. Introducing FrontierHarness Eval. 🧵
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