Prompt Engineering Techniques

Go beyond basic prompting. Learn zero-shot, few-shot, chain-of-thought, and system messages to consistently get better AI responses.

Beyond Basic Prompts

You know how to write decent prompts. Now let’s explore the techniques that professionals use to get consistently excellent results.

Zero-Shot: Just Ask

The simplest technique. You give the AI a task with no examples:

“Classify this customer review as positive, negative, or neutral: ‘The delivery was late but the product quality is amazing.’”

Works well for straightforward tasks. If results are inconsistent, try the next technique.

Few-Shot: Show by Example

Give the AI 2-3 examples before your actual request:

“Classify these customer reviews:

Review: ‘Absolutely love it!’ → Positive Review: ‘Broke after two days’ → Negative Review: ‘It’s okay, nothing special’ → Neutral

Now classify: ‘The delivery was late but the product quality is amazing.’”

Few-shot is remarkably effective. The AI picks up your exact format, style, and criteria from the examples.

Chain-of-Thought: Think Step by Step

For complex problems, ask the AI to show its reasoning:

“A store has 15 apples. They receive 3 boxes with 8 apples each. They sell 12 apples. How many are left? Let’s think step by step.”

The AI will break it down:

Start with 15 apples
Add 3 × 8 = 24 apples → 39 total
Sell 12 → 39 - 12 = 27 apples

Without chain-of-thought, AI often gets math and logic wrong. With it, accuracy jumps dramatically.

System Messages

System messages set the AI’s behaviour for an entire conversation. They’re like giving your assistant a job description:

System: “You are a concise financial advisor for young professionals. Always explain terms in plain English. Give specific, actionable advice. Never give guarantees about returns. End each response with one action step.”

This shapes every response the AI gives. Most AI apps let you set custom instructions that work like system messages.

Structured Output

Need AI to respond in a specific format? Tell it:

“Analyse this business idea and respond in exactly this format: VIABILITY: [High/Medium/Low] KEY RISK: [one sentence] FIRST STEP: [one sentence] ESTIMATED COST: [range]”

Structured output makes AI responses consistent and easy to use in workflows.

Combining Techniques

The real power comes from combining these:

System message sets the persona and rules
Few-shot examples show the expected format
Chain-of-thought ensures thorough reasoning
Structured output makes the response usable

Practice: Take a task you regularly use AI for. Try it with zero-shot, then few-shot, then chain-of-thought. Compare the results — you’ll see a clear quality improvement with each technique.