One prompt line cuts LLM output tokens 56% and call costs 33%
gethackteam · x · 2026-10-24
A simple prompt addition — "Minimum words. Strip filler." — cut output tokens from 1,174 to 516 on the same model and task, reducing estimated whole-call cost by 33%. The author's related Caveman project (making the model terse) has 115K stars on GitHub, with code and a blog post linked.
Related event: 'Caveman' Prompt Trick Cuts AI Token Costs by Up to 65%(2 posts)→
More from coding & agent
- Microsoft open-sources Agensh, a decentralized multi-agent harness scaling to 1,024 agents — donglixp · 2026-10-24
- dumbtv strips Fire TV ads and tracking with one command, no root needed — Signalman23 · 2026-10-24
- CodeRabbit CLI v0.9.0 ships cr code for managing cloud agent tasks in terminal — leslysandra · 2026-10-24
- Solo dev turns a school timetable solver into an MCP server for Claude — Wilbek_DK · 2026-10-24
- ChatGPT Sites ships detailed site analytics: dev logs +216% weekly traffic — Dimillian · 2026-10-24
- Gemini Flash-Lite as a meeting copilot brain: real test results, what worked and what broke — DeskSignalAI · 2026-10-24