Prompt engineering sounds technical. It is actually just learning to communicate clearly with AI. The better your instructions, the better the output.
Be specific about format. Do not say write marketing copy. Say write a 100-word product description for our website, highlighting durability and value, in a friendly tone.
Technical Note
Choose technologies that your team can maintain. The best tool is one you'll actually use and improve.
Provide context. AI does not know your business. Include relevant background. Our company sells eco-friendly cleaning products to environmentally conscious homeowners.
Use examples. Show what you want. Here is a product description we liked: [example]. Write something similar for our new product.
Break complex tasks into steps. Instead of create a marketing campaign, try first identify target audience, then develop key messages, then suggest channels.
Specify constraints. Budget under $1000. Maximum 50 words. Suitable for LinkedIn. No industry jargon. Constraints focus the output.
"Simple systems that work beat complex systems that don't. Start with reliability, then add sophistication.
Request reasoning. Ask the AI to explain its thinking. This helps you evaluate the output and provides material for follow-up prompts.
Iterate and refine. First outputs are rarely perfect. Build on them. That is good, but make it more concise and add a call to action.
Legacy Systems
- •Siloed data
- •Manual integrations
- •Security vulnerabilities
- •High maintenance costs
Modern Stack
- •Unified data layer
- •API-first design
- •Built-in security
- •Automated maintenance
Create prompt templates. For recurring tasks, develop standard prompts that work. Save time and ensure consistency.
The meta-skill: learning what AI is good at (first drafts, brainstorming, summarizing) versus what it struggles with (facts, nuance, truly creative thinking). Play to strengths.
