AI Memory Part 1 — Chain of Density
Author: .ktg
Chain of Density does more than shorten text. Used properly, it summarizes and condenses as a context extension protocol.
Overview
Reframes Chain of Density (CoD) — typically used for summarization — as a context extension mechanism for LLMs. The key insight: CoD’s value isn’t human readability, but achieving high-fidelity machine recall (9.52/10) for fresh AI instances.
Key Concepts
- Progressive Density Layering (PDL): Iteratively compress text with increasing density targets, each pass evaluated for fidelity
- The Carry Packet: Structured context handoff between sessions — the compressed artifact that carries memory forward
- Cross-model validated: Tested on Claude, Grok-4
- Iterative Density by Experts: Different “expert” compressors for different content types
Results
| Model | Outcome |
|---|---|
| Claude | Solves original context window problem |
| Grok-4 | Strong recall with CoD context |
Next
Part 2: Multi-Layer Density of Experts (MLDoE) — production-ready Context Extension Protocol.