Anthropic shipped 3 tools for async agent work this week. But the most interesting part of Nate B Jones' breakdown isn't the tools. It's what he says about memory.

Claude Code now writes notes to itself between sessions. Auto-memory + auto-dream consolidates them every 24 hours in the background. It's good. But open the same project in Kiro or Cursor and nothing transfers. We built Ogham for that gap. ogham-mcp.dev/blog/claude-auto-memory/

Tested Gemini Embedding 2 at four MRL truncation points: 3072, 1536, 768, 512 dims. The scores went UP as I compressed. 512 dims outperformed 3072 on every single query. Rankings stayed identical. Full results: ogham-mcp.dev/blog/gemini-embeddings-multimodal/

Ran 400 memory retrieval questions BEAM benchmark against pgvector. No knowledge graph, no reranker, no LLM at search time. Our retrieval found more gold evidence than the best LLM (Llama-4 + LIGHT) could use. In 9 out of 10 categories. #ai #memory Full results: ogham-mcp.dev/blog/beam-benchmarks/

I built an open-source MCP server that gives AI agents shared memory across clients. Store something in Claude Code, search for it from Opencode, Cursor. No LLM needed, just Postgres + embeddings model. MIT licensed. #opensource #ai #memory github.com/ogham-mcp/ogham-mcp