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Lore is an open-source tool that stores team decisions as typed Markdown files and serves them deterministically to coding agents (like Claude Code, Cursor) via MCP, ensuring agents follow documented requirements instead of guessing.
Anthropic's science blog argues that AI progress in biology lags behind coding because biological data infrastructure is not designed for agents. A case study shows that adding a deterministic retrieval layer (gget virus) boosts accuracy to nearly 100%.
Anthropic researcher Laura Luebbert argues that biological data infrastructure needs to be redesigned for AI agents, using a case study where even strong models failed to reliably retrieve sequence data from NCBI Virus until a deterministic retrieval layer was added.