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Agentic coding systems face rising costs from wasted context and tokens as sessions grow long. Blast Radius introduces a predictive memory management system that estimates how far an incoming prompt will reach across context and code, enabling reversible eviction of unneeded information while identifying recurring redundant transcripts for permanent removal. This has direct applications for reducing operational costs in AI coding assistants and agentic development tools, where efficient context management directly impacts affordability and performance. Tested across seven OpenAI models, the approach meaningfully cut token consumption while maintaining reversibility, supporting more sustainable large-scale agentic coding workflows.
Paper: https://arxiv.org/abs/2608.07440





