Caching and Multi-Level Storage: Don't Let AI Blindly Hit the Database

Wed, 12 Aug 2026 00:00:00 +0000

When AI writes business code, it has a very typical tendency:

async def get_user(user_id: int):
    return await user_db.get_by_id(user_id)

Functionally correct. But if every read in the project becomes:

Read user → Database
Read permissions → Database
Read model → Database
Read Agent → Database
Read knowledge base → Database
Read config → Database

The system soon enters a state where:

Every function is correct, yet the overall architecture grows increasingly inefficient.

The problem is not merely “whether there is a cache”, but:

The AI never first asks: what I want to reuse — a “value”, or an “already-built runtime object”?

This is exactly what’s most worth borrowing from miniagent’s current caching architecture.

It doesn’t just build one cache — it explicitly splits into two categories:

Object Cache
Object caching

Value Cache
Value caching

These two solve fundamentally different problems.

Cache on Interesting AI