Why it matters
Memory and retrieval are where agent prototypes usually fall over. The lab covers agent loops, tool use, vector queries and storing state so an agent keeps context between sessions, with starter templates to take home.
The tokenmaxxing angle
The page itself notes that agents without durable memory repeat themselves and get costlier per conversation. Persisting state instead of resending full history is a concrete way to cut input tokens, so bring a context-size question.
From the organizers
Led by MongoDB Sr. Solutions Architect Samadnya Kalaskar; the lab uses LangGraph plus Atlas Vector Search and runs in the browser. Registration is approval-only; AI After 5 is a women's community with 500+ members, open to all.