Why It Matters

CoreTex makes memory retrieval an economic optimization problem under a fixed substrate budget.

The useful signal is not that a miner can store more text. The signal is that a miner can decide what compact retrieval structure improves future hidden-query performance under temporal drift, distractors, relation depth, and hard capacity limits.

In this framing, the persistent agent state is not a single local model, a hosted context window, or one miner's machine. It is a shared, on-chain-rooted memory substrate that many miners and many models can improve, inspect, and reuse over time.

That maps to practical agent memory design:

• Retrieval quality matters more than storage volume.
• Temporal truth requires stale-memory rejection, not just recall.
• Multi-hop memory needs relation structure.
• Compression pressure exposes which memories and routes are actually useful.
• Public replay makes claimed memory improvements auditable.

If the corpus keeps expanding and the evaluator remains pinned and retrieval-native, CoreTex creates a measurable path for miners to improve a shared memory substrate over time.