I spent three days last month rewriting a system prompt for a code-review agent. Tried persona frames, XML structure, numbered constraints, the works.
Every prompt engineering tutorial from the last three years drilled the same lesson: show the model what you want.
I audited a scoring pipeline last week that was sampling every request twenty times and taking the majority vote.
Something about prompt engineering has been bugging me. We tell people "make the model think step by step" as if that's always the right advice.
The best prompt I wrote last week was terrible. Vague, underspecified, no style reference, no artist name.
Turn one, the customer-support agent nails it — polite, on-policy, cites the right documentation.
Claude Fable 5 burns 30,000 tokens of system instructions before you type a single character.
Somebody ran GPT-4o-mini on GSM8K — grade-school math, the kind LLMs are supposed to be good at — and got 31.8% accuracy.
Three years ago, a paper called EmotionPrompt showed that appending emotional stakes to prompts — phrases like "This is very important to my career!
Three teams ran the same experiments this year and landed on the same uncomfortable result: moving information around inside a prompt — without changing a...
Three days ago, Anthropic shipped Claude Opus 4.8.
Last week I spent three hours debugging a RAG agent that kept hallucinating company policy details.
You shipped the guardrails. You added the system prompt hardening, the input classifiers, the output filters.
Ask GPT-5 "What causes rust on steel?" and you'll get an answer in under a second.
Last month I added chain-of-thought prompting to a medical Q&A pipeline. Hallucination rate dropped.
Everyone loves structured outputs. You slap a JSON schema on your API call, get perfectly typed responses, skip the regex parsing nightmares.
Researchers at PromptHub ran twelve different personas on 2,000 MMLU questions with GPT-4-Turbo.
You write a prompt. You test it.
Claude Opus 4.5 scores 45.
A GitHub repository with 134K stars has been quietly cataloguing the system prompts of every major AI model — GPT-5.4, Claude Opus 4.