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): https://slack.flyte.org/
• ​​​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).