The Judgment Layer

Persistent memory for AI agents is becoming a commodity. The funded field — Mem0, Zep/Graphiti, Letta, Cognee, LangMem, and now platform offerings like Cloudflare’s Agent Memory — handles extraction and provenance well. But agent memory breaks down into four steps: extract what happened, attribute where it came from, judge what it means, and govern how it changes behaviour — and every shipping system stops after step two. Recent formal work (Roynard, 2026) identifies the same missing tier and reports near-zero contradiction-resolution across the field. I stake four claims about that empty rung. One: memory should be shaped like attention — a tree of focus sessions with depth-proportional compression — not shredded into atomic facts. Two: continuity belongs to the judgment layer, not the model — treat the LLM as stateless by design and identity survives model swaps, context compaction and provider churn. Three: typed persistence needs an ignorance ledger — a first-class store for known unknowns, with suspension of judgment (epochē) as a routing outcome alongside accept and refuse. Four: the layer that turns memory into behavioural guidance has to be constitutionally governed — promotion gated on evidence rather than user approval, amendment restricted to the human owner, and no agent ever self-ratifying the law that governs it. I finish with an evaluation protocol — architectural property tests plus a continuity test I call the ache test — and an open invitation to tear it apart.

Status: architecture and evaluation protocol. A results paper follows the build.