Packs

1 pack

Build RAG Pipeline with Pinecone

Build a production RAG pipeline and persistent agent memory using Pinecone as the vector database backend.

6 skills · pack

Results for “persistent-agent”

5 skills

Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend.

Provides persistent, compounding memory for AI agents across sessions using local markdown files, with optional Supabase-backed semantic search.

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Designs persistent memory architectures for AI agents, covering cross-session knowledge retention, entity tracking, temporal validity, graph/vector retrieval, and memory consolidation.

16.9k · bundle

iterative-retrieval

Progressively refines context retrieval in multi-agent workflows to solve the subagent context problem.

Provides persistent, self-hosted semantic memory for AI agents via MCP, storing worklogs, decisions, and notes in PostgreSQL with pgvector for meaning-based retrieval across sessions.