An Art, a Science, or Your Next Job Title?
summary
Claims that generative AI already has over 1 billion users, shows a concrete marketing automation prompt that returns a JSON object for downstream processing, and demonstrates a local run of LLM Linga achieving 177% compression on a prompt with negligible quality loss. Pricing examples cite GPT‑4 at about $60 per million tokens and recommend a model‑selection downgrade strategy, chain‑of‑thought “think step by step” fixes for math errors, and RAG + vector retrieval for reducing hallucinations.
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chapters (11)
- 0:00Introduction and Speaker Background
- 0:51The Rise of Generative AI
- 2:42Understanding Prompt Engineering
- 5:00Prompt Components and Anatomy
- 8:29Tokenization and Cost Efficiency
- 13:34Model Selection Strategies
- 19:42Advanced Prompt Engineering Techniques
- 20:00Tools for Prompt Engineering
- 29:57Handling Hallucinations and RAG Pattern
- 38:41Future of Prompt Engineering
- 39:51Conclusion and Call to Action
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