Vector stores for RAG & Agent Context- AI Build & Learn #6

​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 building with Vector Storage and Search for RAG or Agent context applications.

​No specific vector database was selected, so you can use whichever one you want. I've found that most of the time they're very similar in functionality.

​Here are a few popular ones you can look up to start using:

• ​Chroma

• ​Weaviate

• ​Pinecone

• ​Qdrant

​Resources

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

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

• ​​​Slack (Discuss during the week): Flyte Slack Group

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

​​​In this stream

• ​​​​AutoResearch

• ​​​​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).