LLM bullshit knife, to cut through bs
RAG -> Provide relevant context Agentic -> Function calls that work CoT -> Prompt model to think/plan FewShot -> Add examples PromptEng -> Someone w/good written comm skills. Prompt Optimizer -> For loop to find best examples.
Recent articles
- LLM 0.22, the annotated release notes - 17th February 2025
- Run LLMs on macOS using llm-mlx and Apple's MLX framework - 15th February 2025
- URL-addressable Pyodide Python environments - 13th February 2025