Cognee: Open-source Memory Layer for AI Agents - AI Build & Learn #9
Details
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 Cognee, an open-source memory layer for AI agents that combines vector search and graph databases into a single queryable knowledge infrastructure.
We'll explore how Cognee unifies data from multiple sources, the core API (`remember`, recall, forget, improve), and how persistent agent memory differs from one-shot RAG retrieval.
Some things to look up to get started:
- Cognee GitHub: https://github.com/topoteretes/cognee
- Cognee docs: https://docs.cognee.ai/
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
- Intro to topic
- 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).