Agent OS is an open-source, local-first AI project operating system. It coordinates specialized agents to plan, build, verify, recover, and ship real software—with persistent memory, browser evidence, and real deployment integrations.
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Maker
📌
Hi Product Hunt 👋
I’m Eric, the maker of Agent OS.
Agent OS started as a personal attempt to understand what it would take for AI agents to work on real software projects—not just write code or run commands, but carry a project through planning, execution, verification, recovery, and delivery.
It's an open-source, local-first AI project operating system that runs on your own machine and works directly with real project files.
Instead of placing everything inside one opaque agent loop, Agent OS coordinates a set of specialized agents and keeps their work visible through persistent project memory, structured run records, file changes, command results, browser screenshots, verification evidence, and recovery history.
Some of the current capabilities include:
• Multi-agent planning and parallel execution
• Persistent project memory and local document retrieval
• Bounded coding, review, research, and browser workflows
• Interactive Playwright verification with screenshots and runtime evidence
• Typed failure recovery with explicit safety boundaries
• Git and GitHub delivery workflows
• Vercel, Supabase, and Stripe integrations
• Local previews, deployed links, and traceable final artifacts
The project is local-first and open source under Apache 2.0. The current release is v1.0.0, and it can be installed on Windows with one command:
irm https://raw.githubusercontent.co... | iex
Agent OS is still an early project rather than a polished commercial product. I built it mainly to explore how agent systems can become more reliable, reviewable, and useful for real engineering work.
I’d especially appreciate feedback on:
• Whether the product model is understandable from the interface
• Which parts of the workflow feel genuinely useful
• Where the trust and approval boundaries still feel unclear
• What you would need before using something like this on your own projects
Thanks for taking a look. I’ll be here throughout the launch to answer questions and learn from your feedback.
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Local-first with actual deployment hooks is a nice change from the usual cloud-only agent demos. Curious how the persistent memory holds up once a project gets messy.
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Maker
@cansutokmalosf Thanks! I also think personal agents should run locally, while cloud platforms serve as external connectors.
The memory engine is what coordinates memory system and real project state. After each meaningful chat or task, the engine judges whether something deserves to be persisted into memory, then applies structured, concise updates to relevant memory files (based on run artifacts and other real evidence). So even when the project gets messy the memory usually won't get too messy :)
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Would love a built-in dashboard showing which agents are working, what they've completed, and where they got stuck in real time, so I can step in without digging through logs. That kind of visibility would make complex multi-agent runs way easier to trust and debug.
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Maker
@ferhat160021 Good advice. Visibility is truly important for multi-agent systems, especially when managing the status of different agents at the same time. Will add this feature to future versions!
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Spent an hour with Agent OS and the persistent memory across sessions is genuinely useful, not just a gimmick. Surprised how well the browser evidence step caught a bug my own code review missed.
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Maker
@muratftfl Wow thanks for having a try! Glad to hear that the memory system and browser verification are truly useful for real software projects. These are the core features I'm putting effort in, to give the system more long-term reliability.
Local-first with actual deployment hooks is a nice change from the usual cloud-only agent demos. Curious how the persistent memory holds up once a project gets messy.
@cansutokmalosf Thanks! I also think personal agents should run locally, while cloud platforms serve as external connectors.
The memory engine is what coordinates memory system and real project state. After each meaningful chat or task, the engine judges whether something deserves to be persisted into memory, then applies structured, concise updates to relevant memory files (based on run artifacts and other real evidence). So even when the project gets messy the memory usually won't get too messy :)
Would love a built-in dashboard showing which agents are working, what they've completed, and where they got stuck in real time, so I can step in without digging through logs. That kind of visibility would make complex multi-agent runs way easier to trust and debug.
@ferhat160021 Good advice. Visibility is truly important for multi-agent systems, especially when managing the status of different agents at the same time. Will add this feature to future versions!
Spent an hour with Agent OS and the persistent memory across sessions is genuinely useful, not just a gimmick. Surprised how well the browser evidence step caught a bug my own code review missed.
@muratftfl Wow thanks for having a try! Glad to hear that the memory system and browser verification are truly useful for real software projects. These are the core features I'm putting effort in, to give the system more long-term reliability.