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Explores the use of monoids for embarrassingly parallel data processing, showing that traditionally sequential algorithms like Horner rule and Boyer-Moore majority voting can be parallelized via monoid composition. Also introduces vertical monoid composition for efficient nested grouping-aggregation.
The author details their experience building a custom agent loop using a small local model (Qwen3.5 9B) with structured workflows and a map-reduce pattern to manage context limits, replacing Claude Code for most tasks.