From Cell Tower Climber to AI Architect: Building VAC Memory System with 80.1% LoCoMo Performance
By
ViktorKuz
Hot, fresh, and worth queueing round the block for.
Summary
The article describes a personal journey from being a cell-tower climber and handyman to becoming an AI architect in just 4.5 months through intensive learning with Claude CLI. The author built the VAC Memory System, a state-of-the-art Retrieval-Augmented Generation (RAG) system achieving 80.1% LoCoMo (Long Context Memory) performance on gpt-4o-mini. The system features proprietary MCA (Memory Context Attention) ranking, costs less than $0.10 per million tokens, and maintains 100% accuracy. The content appears to be a GitHub repository or project documentation page with various GitHub product links and developer workflow tools listed.
Key quotes
· 4 pulledFrom cell-tower climber & handyman to AI Architect in 4.5 months via Claude CLI
Built VAC Memory System: SOTA RAG (80.1% LoCoMo) on gpt-4o-mini
Proprietary MCA ranking, <$0.10/M cost, 100% accuracy
Write better code with AI - GitHub Copilot
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