#prompt-engineering

Articles tagged with #prompt-engineering

Chain-of-Thought Prompting, Explained Simply
Here is what most AI tutorials will not tell you about chain-of-thought prompting: the model is not explaining its reasoning to you. It is doing its reasoning by writing it out. That distinction chang
Apr 11, 202618 min read
How to Write Prompts That Don't Drift
Prompt drift is not a bug. It is the predictable decay of mathematical constraint over an extended context window. You give an LLM a precise, 400-word instruction. The first 50 tokens of output are ex
Apr 3, 20267 min read2
LangChain, DSPy, and the Physics of Probability Engineering
A thread on r/PromptEngineering last week opened with a genuinely sharp question: "Is 'probability distribution engineering' just a fancy way of saying 'be more specific'? And isn't that just DSPy run
Apr 3, 202614 min read7
The Probability Theory of Prompts: How Context Shapes LLM Output
Stop talking to Large Language Models. They do not understand you, they do not care about your conversational tone, and they do not "think" about the problem. An LLM is a conditional probability esti
Mar 26, 20267 min read6
Advanced RAG Prompting Strategies
Most RAG systems underperform not because the retrieval is broken, but because the prompt is lazy. You've done the hard architectural work: chunked the documents, built the vector index, wired up sema
Mar 23, 202613 min read15
The One Prompt Rule Nobody Talks About: Resolving Ambiguity for LLMs
How downstream purpose, not length, defines success in AI interaction.
Mar 19, 20269 min read36