21. Prompt Engineering Mastery
The skill that makes or breaks AI productivity: writing prompts that get results.
(Spoiler: "Make it work" is not prompt engineering. Neither is "fix this bug". Be specific or watch AI hallucinate wildly creative nonsense. 🎭)
Core Techniques
1. Zero-Shot
Direct instruction without examples.
"Write a Python function to sort a list"2. Few-Shot
Provide examples to guide output format.
Input: "hello world" Output: "HELLO WORLD" Input: "foo bar" Output: "FOO BAR" Input: "test string" Output:
3. Chain-of-Thought
Ask AI to explain reasoning step-by-step.
"Think step-by-step: How would you optimize this query?"4. Role Prompting
Define AI's expertise/perspective.
"Act as a senior backend architect. Review this API design..."Advanced Patterns
- Constrained Output: "Output only valid JSON, no markdown"
- Iterative Refinement: Build complexity gradually
- Meta Prompting: Ask AI to write better prompts
- Negative Prompting: "Do NOT use deprecated APIs"
Common Mistakes
- ❌ Too vague: "make it better"
- ❌ No context: paste code without explaining what you want
- ❌ No constraints: letting AI decide critical details
- ✅ Specific: "Refactor to use async/await, preserve error handling"