The recurring friction in my agent workflow is not typing speed. It is context loss.
I switch between coding CLIs, restart a session, or hand a task to another agent vendor, and suddenly the useful decisions are trapped in the previous conversation. Reconstructing that state costs more time than the original investigation.
akitaonrails/ai-memory addresses that narrow problem: persistent memory for coding agents and a shared handoff point between different tools. That simplicity is what caught my attention. It is not trying to become another full orchestration layer.
The minimal setup
I keep the repository beside my other local developer tools and build the Rust binary in release mode:
