🧠 Memory That Doesn't Reset — Jarvis actually knows me¶
I mentioned to Jarvis once, in a throwaway sentence in April, that I'm allergic to shellfish. In July, when I asked it to help me pick a restaurant for my partner's birthday, it volunteered "you'll want to filter for menus that have non-shellfish options" — without being reminded, in a totally different conversation, on a different topic.
That's not magic. The trick is that Jarvis writes to three plain markdown files in my home directory whenever it learns something worth remembering:
SOUL.md— how I want it to behave (tone, length, what to push back on)MEMORY.md— facts about me, my projects, my preferencesUSER.md— who I am: my role, my team, my context
Every new conversation starts by reading those three files. I can open them in any text editor. I can delete a line and the memory is gone. The whole thing is ~6 KB of markdown. No vector DB, no embedding cache, no opaque "personalization layer."
Why it's nice¶
- It's auditable. I can read what Jarvis "knows" about me in 30 seconds. Most personal-AI products literally can't tell you.
- It's portable. I keep my three files in iCloud Drive. When I set up Jarvis on a new machine, my memory comes with me — without re-onboarding.
- It compounds. After two weeks Jarvis stopped re-asking what my code style is. After six weeks it stopped re-asking who's on my team. The conversations get shorter because the context is already there.
- It can't drift. Vector retrieval can confidently surface the wrong "memory" and you'd never know. Plain markdown that I can read can't lie about what it contains.
How I set this up¶
→ User Guide: Agents explains the persistent-agent pattern, including how SOUL.md / MEMORY.md / USER.md are loaded at conversation start.
→ Tutorial: Deep Research Assistant uses the same persistent-memory primitive — a good place to see it in action with code.