Welcome to the official GitHub page for Daytona Experiments!

Daytona is a secure, scalable runtime for AI-generated code execution and agent workflows. Our open-source platform provides lightning-fast infrastructure (200ms startup) with complete isolation, giving developers and AI systems a safe sandbox for running generated code without risk. The comprehensive Daytona SDK offers programmatic control over workspace creation, file operations, and process execution—essential components for building robust AI agents with dynamic lifecycles.

Daytona Enterprise delivers production-ready infrastructure for organizations building AI applications with enterprise-grade security, compliance tools, and flexible deployment options. Our stateful environment snapshots enable persistent agent operations across sessions, making Daytona the ideal foundation for Fortune 500 companies and startups implementing AI agent architectures.

Daytona Experiments is an initiative under the Daytona designed to foster experimentation and innovation among external collaborators, including students, researchers, and tech enthusiasts. By providing a structured environment and the necessary resources, we aim to empower individuals to conduct meaningful experiments and contribute to the broader tech community.

• Empower Innovators: Provide a platform for individuals to initiate and execute innovative experiments.
• Facilitate Collaboration: Foster a collaborative environment where knowledge and resources are shared.
• Encourage Learning: Promote learning through hands-on experience and experimentation.

We welcome collaboration from external contributors! If you are interested in joining our organization and conducting an experiment, please follow these steps:

1. Contact Us: Reach out to us via our community Slack
2. Onboarding: Upon approval, you will be invited to join the daytonaio-experiments GitHub organization.
3. Experiment Proposal: Submit your experiment proposal for review.
4. Repository Creation: Once approved, we will create a new repository and assign it to you.
5. Weekly Checkpoints: Participate in regular weekly checkpoints where you will present your work. Based on the reviews, you will either receive approval to continue or be advised on necessary adjustments.
6. Offboarding: Complete your project after successfully passing all checkpoints. If you fail to meet the criteria at any checkpoint, the offboarding process will be initiated.