LLMs don’t have a memory problem. They have an architecture problem.

An open research series in a prologue and eight parts. Each part publishes the architecture before the code. Then the code and the measurements correct it. Every stage borrows from an architecture that has already proven itself, without copying it whole.

Read in order

What the series rediscovers

It does not only move forward. It comes back to its own ideas, sometimes loses them, and finds them again by measuring.

April 2025 → April 2026

The prologue already held the hierarchy

Context Cascade’s four levels, queried one after another, are a cache hierarchy. They get the vocabulary a year later with the APU, and the metadata search becomes BMJ.

April → August → October 2026

The user never waits for memory

Set by Agent OS and the APU scheduler. Lost in the Akili rewrite, where extraction takes a third of the turn. Found again by measurement, then priced at 34.6% of perceived latency. Still an open decision.

January → October 2026

Urithi returns to UCCE

Memory scoped to a context, a source for every fact, memory the person can see: all of it was in User-Centric Context Engineering. TencentDB Agent Memory was a reminder, not a source.

Method

Proved, not claimed

Theory first

The architecture is published before the code, to be defended before anyone is attached to it.

Code the next day

Article on 15 March, repository on 16 March. Article on 17 July, repository on 18 July.

Every number measured

On the real implementation, with its date, commit and model, and the command that reproduces it.

Say what it doesn’t show

Each measurement article ends on its limits. The tests carry hundreds of deliberate defects they must catch.