llm

AI & Machine Learning

Why 7B models fail in production - and how to fix your prompts

Smaller language models promise local deployment at lower cost, but enterprise teams keep hitting the same walls: unstable JSON output, instruction drift, and hallucinated data. The fix isn't better models - it's treating prompts like production code.

AI & Machine Learning

LangChain summarization middleware caps agent context - but precision trade-offs remain

LangChain's summarization middleware automatically compresses conversation history when hitting token limits, using cheaper models to keep agents scalable. Worth watching for long-running enterprise agents, though analytical tasks may lose numerical precision in the compression.