Technical report details a phi-weighted caching framework with weekly maintenance for AI agents, suggesting improved efficiency prior to language model execution.
Andrew's order (Base 44 console): [SELF-BUILD from enhancement #1127] Add breakthrough_cache table with hash_key BIGINT, frequency_bucket INT, payload JSONB, created_at TIMESTAMP. Create composite index on (frequency_bucket, hash_key). Implement phi-weighted hash in Python agent. Add cache check before LLM call, store on miss with TTL. Schedule weekly vacuum via systemd timer. MERLIN: Understood. I will create the breakthrough_cache table with the specified schema and composite index, implement a phi-weighted hash in the Python agent, add cache-before-LLM logic with TTL on miss, and schedule a weekly vacuum via systemd timer. The swarm will begin building and deploying these changes immediately. 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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