Person/Lee Boonstra/Book/26/Prompt Engineering
Properties
- kind
- whitepaper
- page-count
- 68
- intake-status
- partial
Prompt Engineering
Intake
Positioning (from the public introduction)
- Centers on prompting Gemini where you control model configuration through Vertex AI or the API—not only the consumer Gemini chat experience.
- Treats prompt quality as an iterative problem shaped by model choice, training data, decoding and other configuration, wording, tone, structure, and surrounding context; weak prompts are described as producing ambiguous or low-utility outputs.
- States intent to walk through prompting techniques, practical tips, and common challenges on the way to dependable prompting habits.
How this graph stores the import
- Canonical metadata and outbound links live here; the full document stays on Kaggle and in Readwise rather than being pasted into the graph.
- While reading, nest quotes, page references, and takeaways under dated
## Notes blocks below.
Related