Pieces runs on-device via its proprietary LTM-2 (Long-Term Memory Engine), which captures OS-level context across every application and forms structured, time-indexed memories from code, documents, browser activity, and conversations. It integrates with developer tools through a plugin layer (VS Code, Chrome) and exposes a Model Context Protocol (MCP) interface, enabling deep memory injection into LLMs like GitHub Copilot, Claude, Cursor, and Goose. The architecture is air-gapped by default — no data leaves the device unless explicitly permitted — and supports both local and cloud LLM providers, including bring-your-own-key configurations. Developers can search memories via natural language, time-based queries, or semantic tags auto-generated by the AI layer.