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AgentOS
Rust runtime for AI agents with time-travel replay
AgentOS is a Rust runtime layer that sits underneath agent frameworks instead of replacing them. One command gives you a supervised agent process, a health endpoint, a gRPC message bus, a live SSE event stream and a journaled trace. Every LLM exchange and tool result is recorded at the provider boundary, so any run replays deterministically with no API cost. Open source, local-first, currently alpha.
Hey Product Hunt, I'm Wahib, the maker.
Most agent tooling helps you build a workflow. My problem started after that: the workflow had to run as a long-lived process, fail clearly, restart carefully, and stay inspectable afterwards. Debugging step 7 of a run meant paying for real API calls again, and never getting the same behaviour twice.
So AgentOS journals every LLM exchange and tool result at the provider boundary. `agentOS replay` re-runs a session offline with the recorded responses and reports drift.
One process also gives you supervision, a health endpoint, a gRPC bus, an SSE event stream and secret isolation via a vault crate. It is built in Rust and designed to sit under LangGraph, AutoGen, CrewAI or your own agents rather than replace them.
Being honest about the stage: the run / ps / logs / trace / replay CLI flows are stable locally. `agentOS fork` (branching a run from a checkpoint) is scaffolded but not implemented yet — that's what I'm building next, along with the dashboard, WASM plugin runtime and stronger restart guarantees.
One question I would love answers to: if you run agents today, what breaks first for you — supervision, observability, or reproducing failures?
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About AgentOS on Product Hunt
“Rust runtime for AI agents with time-travel replay”
AgentOS was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #40 on the daily leaderboard. AgentOS is a Rust runtime layer that sits underneath agent frameworks instead of replacing them. One command gives you a supervised agent process, a health endpoint, a gRPC message bus, a live SSE event stream and a journaled trace. Every LLM exchange and tool result is recorded at the provider boundary, so any run replays deterministically with no API cost. Open source, local-first, currently alpha.
AgentOS was featured in Developer Tools (517.6k followers), Artificial Intelligence (476.1k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 220.8k products, making this a competitive space to launch in.
Who hunted AgentOS?
AgentOS was hunted by Wahib | Software Developer. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Wahib | Software Developer