Reduce LLM token and context waste during long coding sessions

Reduce LLM token and context waste during long coding sessions targets a $10.0B = 25M developers x $400 ARPU/year on LLM-assisted developer tooling and optimization total addressable market with medium saturation and a year-over-year growth rate of 40-60% annual growth in LLM-assisted developer tooling adoption.

Key trends driving demand: LLM-assist adoption -- more developers rely on models for coding, increasing per-session token usage and costs.; Plugin ecosystems -- hosted coding assistants (Claude Code, Copilot, Replit) now support plugins, making lightweight integrations viable.; Cost-conscious teams -- as model usage drives spend, teams seek tools to optimize token consumption and maintain session continuity.; Model capability increases -- larger context windows are common but come with rising compute costs, so compression/summary tools remain valuable..