{
  "version": "1.0",
  "type": "rich",
  "title": "AI Prompt Engineering 2024: Techniques That Work",
  "author_name": "Sebastien Rousseau",
  "author_url": "https://sebastienrousseau.com/about/",
  "provider_name": "Sebastien Rousseau",
  "provider_url": "https://sebastienrousseau.com/",
  "thumbnail_url": "https://cloudcdn.pro/stocks/images/ai-prompt-engineering-modern-office.webp",
  "thumbnail_width": 1200,
  "thumbnail_height": 630,
  "html": "<blockquote class=\"oembed-card\"><p><a href=\"https://sebastienrousseau.com/2024-01-23-advancements-in-ai-prompt-engineering/\">AI Prompt Engineering 2024: Techniques That Work</a></p><p>Prompt engineering structures LLM input at inference time — no weight updates required. This article covers the techniques that proved reliable in 2024: zero-shot task framing (Brown et al., 2020), chain-of-thought reasoning (Wei et al., 2022), self-consistency sampling (Wang et al., 2022), ReAct agent loops (Yao et al., 2022), indirect prompt injection risk (Greshake et al., 2023), and applied RAG patterns from financial services.</p><p><cite>Sebastien Rousseau — sebastienrousseau.com</cite></p></blockquote>",
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  "height": 240,
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}