Reinforcement Learning with OpenEnv - AI Build & Learn #3

​Welcome to AI Build & Learn a weekly AI engineering stream where we pick a new topic and learn by building together.

​​This event is about Reinforcement Learning with OpenEnv. OpenEnv is a e2e framework for creating, deploying and using isolated execution environments for agentic RL training, built using Gymnasium style simple APIs.

​https://github.com/meta-pytorch/OpenEnv

​​Resources

• ​​GitHub: https://github.com/sagecodes/ai-build-and-learn

• ​​Events Calendar: https://luma.com/ai-builders-and-learners

• ​​Slack (Flyte AI Slack): https://slack.flyte.org/

• ​​Hosted by Sage Elliott: https://www.linkedin.com/in/sageelliott/

​In this stream

• ​​Reinforcement Learning with OpenEnv

• ​​Hands-on demo

• ​​Community Discussion + practical examples

​​Community challenge (optional)

​​Try spending 30–90 minutes during the week learning or building something related to the topic, then share what you’re working on in Slack.

​​Note on Flyte / Union

​​You may see Flyte used in some demos. Flyte is an open-source AI orchestration platform maintained by Union (where I work) for building scalable, durable, and observable AI workflows. You do not need to use Flyte to participate.

• ​​Union: https://www.union.ai/

• ​​Flyte: https://flyte.org/

​​Drop a comment with ideas for future topics (agents, RAG, MLOps, robotics, frameworks, and more).