Prompt Engineering for Testers: Types and Applications
summary
Covers concrete prompt patterns—start with instructional verbs, add a role and 1–N examples to move from zero/one/few‑shot to better outputs—demonstrates Chain of Thought, self‑consistency and Tree of Thoughts for stepwise reasoning, and shows that diverse examples measurably improve accuracy. Shows tools: PromptsRoyal for generating and scoring prompts and OpenAI Playground (uses GPT‑3.5‑turbo, notes GPT‑4 access/16k context limits). Ends with practicable rules: be specific, set constraints and output style, iterate prompts and compare results.
AI-written summary · about
chapters (5)
- 0:00Introduction to prompt engineering
- 3:21Prompting techniques explained
- 6:34Advanced prompting methods
- 10:29Tools for prompt development
- 14:23Best practices for testers
related talks
47mThe Art of Prompt Engineering: Best Practices for Effective AI Interactions
44mSupercharge Your Productivity Mastering Prompt Engineering
02h 01mPrompt Engineering and AI Red Teaming
01h 08mIn Prompts We Trust
14mPrompt Engineering is Dead
29mSupercharge Your Productivity: Mastering Prompt Engineering
18mTechniques for Enhanced Model Performance
13mPrompt Engineering Simplified