This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
PandaOS
One local AI workstation for your entire workflow.
PandaOS is a local AI workstation that brings code, terminal, browser, deployments, data, apps, and AI agents into one place. Run workflows across tools, manage multiple projects, and hot-swap AI plans without losing context.
We built PandaOS because our AI tools kept getting better, but our actual workflow didn’t.
Code in one place. Terminal somewhere else. Browser, deployments, databases, email, GitHub, another AI tool… and somehow you’re still the one carrying context between all of them.
We got tired of being the glue.
So we built PandaOS: a local AI workstation where your code, tools, apps, projects, and AI agents can live and work together.
The idea is simple: AI shouldn’t stop after writing the code. It should be able to operate the work around it too.
With PandaOS you can:
Run workflows across code, browser, deployments, databases, email, and connected apps
Manage multiple projects without constantly rebuilding context
Save reusable agent workflows for repetitive tasks
Keep persistent project knowledge locally
Connect your own AI subscriptions, API keys, and local models
Hot-swap between AI plans when one hits its session limit without starting the conversation over
One of our favorite examples starts with a bug report in an email. Panda reads it, finds and fixes the code, opens the browser to verify the fix, deploys it, and drafts the reply, all inside the same environment.
That’s the kind of workflow we think AI should be able to handle.
PandaOS is free to start, with no credit card required, and we’re still building quickly.
We’d especially love feedback from developers, founders, and builders already living across tools like Cursor, Claude Code, GitHub, Vercel, Supabase, terminals, and way too many browser tabs.
What still feels fragmented in your workflow? That’s probably the most useful thing you could tell us.
The other co-founder here, and the one who doesn't write code.
Ric built PandaOS for people living across code, terminal and deployments. I've ended up running the whole business side of the company in it: investor outreach, our pipeline, the data room, team status across a dozen projects, email, calendar. My "team" is a handful of agents and small apps I described in chat. None of them needed a line of code from me.
The bug-to-deploy workflow Ric describes is the developer version. My version starts with a Monday morning: it reads what came in over the weekend, updates project status, drafts the follow-ups and tells me what actually needs me. Same product, same local setup, just a different job.
So if you're a founder or operator reading this and thinking "nice, but I'm not a developer": that was me nine months ago. Try it with one real task you'd normally do by hand.
And Ric's question stands for you too. What still feels fragmented in your day? That's the feedback we'll actually build on.
Big congratulations to the pandaOS team on the launch! We have been all using around the office nonstop and to me its a big improvement to claude code/ codex. I think having your agentic coding tool be model-agnostic is going to be more and more important in the future. And the UI implementation of all the different MCPs is a big step up over Claude Code/ codex as well. Good luck on the launch!
Been playing around with PandaOS and honestly, it's pretty amazing what the team is building.
I use a bunch of different AI and dev tools, so having everything in one place just makes sense.
Congrats on the launch guys! 🐼🚀
About PandaOS on Product Hunt
“One local AI workstation for your entire workflow.”
PandaOS was submitted on Product Hunt and earned 16 upvotes and 4 comments, placing #35 on the daily leaderboard. PandaOS is a local AI workstation that brings code, terminal, browser, deployments, data, apps, and AI agents into one place. Run workflows across tools, manage multiple projects, and hot-swap AI plans without losing context.
PandaOS was featured in Developer Tools (521.6k followers) on Product Hunt. Together, these topics include over 89.4k products, making this a competitive space to launch in.
Who hunted PandaOS?
PandaOS was hunted by Riccardo Destratis. 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.
Want to see how PandaOS stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Riccardo Destratis
Hey Product Hunt 👋
We built PandaOS because our AI tools kept getting better, but our actual workflow didn’t.
Code in one place. Terminal somewhere else. Browser, deployments, databases, email, GitHub, another AI tool… and somehow you’re still the one carrying context between all of them.
We got tired of being the glue.
So we built PandaOS: a local AI workstation where your code, tools, apps, projects, and AI agents can live and work together.
The idea is simple: AI shouldn’t stop after writing the code. It should be able to operate the work around it too.
With PandaOS you can:
Run workflows across code, browser, deployments, databases, email, and connected apps
Manage multiple projects without constantly rebuilding context
Save reusable agent workflows for repetitive tasks
Keep persistent project knowledge locally
Connect your own AI subscriptions, API keys, and local models
Hot-swap between AI plans when one hits its session limit without starting the conversation over
One of our favorite examples starts with a bug report in an email. Panda reads it, finds and fixes the code, opens the browser to verify the fix, deploys it, and drafts the reply, all inside the same environment.
That’s the kind of workflow we think AI should be able to handle.
PandaOS is free to start, with no credit card required, and we’re still building quickly.
We’d especially love feedback from developers, founders, and builders already living across tools like Cursor, Claude Code, GitHub, Vercel, Supabase, terminals, and way too many browser tabs.
What still feels fragmented in your workflow? That’s probably the most useful thing you could tell us.
Thanks for checking out PandaOS 🐼