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Cloud infrastructure was built for humans, not AI agents. Adios provides secure, ephemeral sandboxes and native MCP integration. Now your AI can safely write, preview, and deploy code to production without DevOps friction or breaking your systems.
Hey Product Hunt! 👋 I’m Sam, the founder of Adios.dev.
Traditional cloud hosting was designed for a human-first workflow: a developer writes code locally, commits to Git, triggers a multi-minute CI/CD build, and deploys to production once or twice a day.
But as software development shifts from human-only coding to AI-assisted and autonomous agent loops, that infrastructure model starts breaking down.
When an AI agent (like Claude, Cursor, or a custom LLM loop) generates code and wants to test, preview, or deploy it:
- Security is a nightmare: Executing LLM-generated code directly on your local machine or primary backend opens you up to prompt injections and server exploits.
- DevOps overhead: An AI shouldn't have to manage complex Dockerfiles or YAML manifests just to run a test script or spin up a preview.
- Dependency & build friction: Package installations (npm install, pip install) and multi-file builds clutter your local environment and break the agent's real-time flow.
That’s why I built Adios.dev.
Adios gives AI agents and engineering teams isolated, automated environments to write, test, and deploy code safely.
- 🔌 Native MCP Integration: Connect your AI client directly to scoped tools so the agent can inspect project files, run builds, and open preview environments.
- 🛡️ Isolated Previews: Let AI install dependencies and test code in disposable sandboxes without touching your primary infrastructure or breaking production.
- 🛑 Human-in-the-Loop Safeguards: Let AI test and iterate freely, but keep live production releases behind explicit human approval gates.
A quick "building in public" reality check:
I’ll be fully transparent—while provisioning the execution sandboxes is fast, optimizing the hard physics of things like npm install and complex build steps for instantaneous AI previews is an ongoing engineering battle. It's a tough challenge, but we are making it faster every single week.
I’m building this completely solo and would love your brutal, honest feedback.
Question for the community: For those of you building with AI agents or code interpreters today, how are you currently handling secure code execution and previews?
Let's chat in the comments! 🚀
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About Adios.dev - AI Workspace on Product Hunt
“Secure code execution sandboxes for AI agents.”
Adios.dev - AI Workspace was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #119 on the daily leaderboard. Cloud infrastructure was built for humans, not AI agents. Adios provides secure, ephemeral sandboxes and native MCP integration. Now your AI can safely write, preview, and deploy code to production without DevOps friction or breaking your systems.
Adios.dev - AI Workspace was featured in Developer Tools (520.4k followers), Artificial Intelligence (479.9k followers) and Vibe coding (686 followers) on Product Hunt. Together, these topics include over 212.1k products, making this a competitive space to launch in.
Who hunted Adios.dev - AI Workspace?
Adios.dev - AI Workspace was hunted by Sam. 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 Adios.dev - AI Workspace stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Sam