•1 min read•from Towards Data Science
Long Context Isn’t Free — I Built a Safe Prompt-Pruning Layer That Makes LLM Systems Work
LLMs don’t fail because they forget—they fail because they remember too much. As conversations grow, prompts accumulate redundant and low-value tokens, driving up cost and latency while silently degrading output quality. This article introduces a deterministic prompt-pruning layer that reduces token usage without breaking dependencies, backed by real benchmarks and production-tested design.
The post Long Context Isn’t Free — I Built a Safe Prompt-Pruning Layer That Makes LLM Systems Work appeared first on Towards Data Science.
Want to read more?
Check out the full article on the original site
Tagged with
#real-time data collaboration
#big data management in spreadsheets
#generative AI for data analysis
#conversational data analysis
#rows.com
#Excel alternatives for data analysis
#intelligent data visualization
#real-time collaboration
#data visualization tools
#enterprise data management
#big data performance
#data analysis tools
#data cleaning solutions
#LLMs
#Large Language Models
#Prompt Pruning
#Token Usage
#Long Context
#Latency
#Cost Optimization