billion-context keeps coding sessions alive for days

billion-context attacks one of the biggest bottlenecks in agentic coding: context growth, not model intelligence.

• –It sits between coding agents and Anthropic/OpenAI-compatible APIs, making the approach broadly portable.
• –Reversible compression, decompression, and context search are more useful than simply truncating old messages.
• –Smaller active contexts could reduce token costs while preserving high cache-hit rates.
• –The trade-off is summary fidelity: developers should still anchor critical state in tests, commits, and project documentation.
• –Its MIT license includes an additional attribution requirement for products that expose the software to users.