AI Tips & Tricks
Master the art of AI prompting, optimization, and integration with battle-tested techniques from experts worldwide.
Prompting Fundamentals
Be Specific and Clear
Vague prompts yield vague results. Instead of "write code for login," try "create a Next.js server action that authenticates users with email and password using bcrypt, returns session tokens, and handles errors gracefully."
"Make a button"
"Create a primary action button with hover animation, disabled state, and loading spinner"
Provide Context & Examples
Give AI background information, constraints, and examples of desired output. The more context you provide, the better the AI can tailor its response to your specific needs.
// Good example:
"I'm building an e-commerce site. Create a product card component that shows image, title, price, and rating. Use Tailwind CSS and match this existing card style: [paste example]"
Iterate and Refine
First outputs are rarely perfect. Use follow-up prompts to refine results: "Make it more concise," "Add error handling," or "Optimize for performance." Think of it as a conversation.
→ Review output
Refinement 1→ Getting closer
Refinement 2→ Perfect!
Use Role Prompting
Frame the AI as an expert in a specific domain to get more targeted responses. "Act as a senior React developer..." or "You are a UX design expert..."
"Act as a senior TypeScript engineer. Review this code for type safety issues and suggest improvements using advanced TS features."
Advanced Techniques
Temperature Control
Temperature controls AI creativity. Lower values (0.1-0.3) produce consistent, factual outputs perfect for code generation and technical tasks. Higher values (0.7-0.9) enable creative, diverse responses ideal for brainstorming and content creation.
Code generation, data analysis, factual answers, API integration
Creative writing, brainstorming, marketing copy, storytelling
Chain-of-Thought Prompting
Ask AI to "think step by step" or "explain your reasoning" to get more accurate results for complex problems. This technique dramatically improves performance on logic, math, and multi-step tasks.
// Example:
"Debug this React component. Think step by step:
1. Identify potential issues
2. Explain why each is problematic
3. Provide solutions with reasoning"
Few-Shot Learning
Provide 2-3 examples of the desired output format before asking for the real task. This "teaches" the AI your exact requirements and dramatically improves output consistency.
// Example 1: Input → Output
// Example 2: Input → Output
// Example 3: Input → Output
// Now do this: [your actual task]
Quick Wins
Use Delimiters
Wrap input data in triple quotes, XML tags, or markdown to clearly separate instructions from content
Specify Output Format
Request "output as JSON," "create a markdown table," or "format as bullet points" for structured responses
Set Constraints
Add limits like "in under 100 words," "using only vanilla JS," or "without external libraries"
Ask for Alternatives
"Give me 3 different approaches" helps you see multiple solutions and choose the best fit
Request Explanations
"Explain why you chose this approach" helps you learn and verify AI reasoning
Negative Prompting
Tell AI what NOT to do: "without using jQuery," "avoid deprecated APIs," "don't include comments"
Common Pitfalls to Avoid
Don't Trust Blindly
Always review AI-generated code. It can produce bugs, security issues, or suboptimal solutions.
Avoid Ambiguity
Unclear prompts lead to guesswork. Be explicit about requirements, constraints, and expected behavior.
Don't Skip Testing
AI-generated code still needs thorough testing, especially for edge cases and error handling.
Avoid Prompt Injection
When building AI apps, sanitize user inputs to prevent users from manipulating your system prompts.