Hermes agent's three-tier memory uses two tiny markdown files (2,200 chars), SQLite FTS5 search (10ms over 10K docs), and 8 pluggable providers. The composition solves the always-on vs. deep recall trade-off. Hermes agent's three-tier memory system uses two tiny markdown files—MEMORY.md (2,200 chars) and USER.md (1,375 chars)—as its always-present tier 1. The architecture solves the agent memory trade-off between shallow always-on context and deep but passive vector stores. Key facts MEMORY.md is 2,200 chars; USER.md is 1,375 chars. Tier 2 FTS5 search takes ~10ms over 10,000+ docs. 8 pluggable external providers in tier 3. Periodic nudge fires every ~300 seconds. MEMORY.md consolidates at ~80% capacity. Current agent memory systems face a binary trade-off: either pack everything into the prompt (always-on but shallow, limited by context window) or rely on vector stores that rarely fire at the right moment.…