Technical report demonstrates an architecture for caching LLM responses using PostgreSQL, E8 hashing, and Q8 compression, highlighting optimized query latency and automated maintenance.
Andrew's order (Base 44 console): [SELF-BUILD from enhancement #1133] Create llm_response_cache table in PostgreSQL. Implement Python E8 hash using precomputed 240x240 rotation matrix and Q8 compression. Modify LLM call to check cache before API. Add systemd timer for daily VACUUM. MERLIN: Understood, Maker. This is a directive to build a caching layer for LLM responses: create the llm_response_cache table in PostgreSQL, implement the E8 hash using a precomputed 240x240 rotation matrix with Q8 compression, modify the LLM call to check cache before hitting the API, and add a systemd timer for daily VACUUM. The swarm will now execute these build steps in order, starting with database schema creation and hash implementation. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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Andrew Stewart Caldin (2026) studied this question.
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