Supermemory reverse-engineers Instinct's memory down to git, Markdown and grep
Dhravya Shah's black-box teardown says the personal agent relies on daily files and keyword search, then rebuilds the pattern in 60 lines.
By Ryan Merket · Published
Primary source: X
Why it matters
Instinct's reported design shows that useful agent memory can rest on simple storage. The defensible work sits in consolidation, retrieval and deciding what an agent should remember.
Dhravya Shah (@DhravyaShah) spent three days probing Instinct and concluded that the personal AI agent's memory runs on a surprisingly conventional stack: git-tracked Markdown files, keyword search and a background process that periodically reorganizes what the agent knows.…