Developer hexiecs released talk-normal on April 8, 2026, a universal system prompt that reduces AI verbosity by 71-73% across major language models without requiring model-specific customization. The project reached 612 GitHub stars within five days by addressing widespread frustration with unnecessarily lengthy AI responses.
Single Prompt Works Across GPT, Claude, Gemini, and LLaMA Models
talk-normal provides a unified system prompt compatible with GPT, Gemini, LLaMA, Claude, and other language models without requiring adjustments for different architectures. The prompt explicitly instructs models to eliminate filler content, corporate-sounding language, and redundant explanations that developers commonly refer to as "AI slop." Testing shows a 73% reduction in response length for GPT-4o-mini and 72% for GPT-5.4.
Concrete Example Shows 67% Character Reduction
The repository includes a documented example where a Python explanation compressed from 1,583 characters to 513 characters. The original response included phrases like "I'd be happy to help" and "Let me explain" followed by multiple paragraphs of background information. The optimized version eliminated these patterns while preserving technical accuracy and useful information.
Active Development With Published Test Results
The project maintains detailed documentation including a changelog, contribution guidelines, and quantitative test results across different models. The repository provides implementation examples for various use cases and programming languages. hexiecs continues active development with community contributions addressing edge cases and model-specific optimizations.
Community Response Highlights Universal Pain Point
The rapid accumulation of 612 stars and feature placement in GitHub trending repositories indicates strong developer demand for concise AI interactions. The project's success stems from offering a simple, copy-paste solution rather than requiring fine-tuning or complex prompt engineering. Users can immediately apply the system prompt to existing workflows without infrastructure changes.
Key Takeaways
- talk-normal reduces AI response length by 71-73% across GPT-4o-mini and GPT-5.4 using a single universal system prompt
- The project reached 612 GitHub stars within five days of its April 8, 2026 release
- A documented example shows Python explanation compression from 1,583 to 513 characters while preserving technical content
- The system prompt works without modification across GPT, Claude, Gemini, LLaMA, and other major language models
- Active development includes published test results, detailed documentation, and community contribution guidelines