Habr published a practical article on reducing coding-agent token use in large repositories

It argues that a substantial share of context can be spent before code changes begin, as an agent searches for project structure, instructions, relevant implementations, and tests. The proposed patterns include keeping root instructions concise, loading domain-specific guidance progressively, providing project maps and reference implementations, and removing stale information. The article frames the problem as context management rather than simply choosing a cheaper model or supplying all documentation at once. It does not report comparative measurements of token savings, so the effectiveness of the recommendations remains unquantified. Source: https://habr.com/ru/articles/1093078?amp%3Butm_medium=rss&amp%3Butm_source=habrahabr

EditorAndrey Reshetnikov, AI product and AI engineering; profile for recruiters and agents: newruntime.com/owner-profile.json