Building Persistent AI Systems Without a Traditional Database
Authors/Creators
Description
This paper shows a new way to build AI assistants without using a complex database. Instead of hiding data in a database, we store the AI’s memory, personality, and skills in simple Markdown files that anyone can read. For systems like personal assistants or those with fewer users, a heavy database is often overkill.
Proper Segregation of markdown files:
- working_memory.md
- episodic_memory.md
- semantic_memory.md
- personality.md
- habits.md
- self_reflection.md
- skills.md
- skill_context.md
To help the AI find information quickly, we use a tool called FAISS to search through these files, but the files themselves always remain the main source of truth.
By using simple files instead of a database, the system is much easier to fix, track, and move. It’s a perfect 'middle ground' for personal AI projects because it’s simple to manage but still powerful enough to handle complex tasks.
Files
Markdown_Native_Architecture.pdf
Files
(37.4 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:dd9ccf7678a3b8dd79450f635ae1d71e
|
37.4 kB | Preview Download |
Additional details
Dates
- Available
-
2026-03-14
Software
- Repository URL
- https://github.com/maluskarhrishikesh-afk/OctaMind
- Programming language
- Python
- Development Status
- Active