KWAS Academy
Learn. Build. Master.
QUICK START:HTMLCSSJavaScriptTypeScriptPythonSQLReactNext.jsNode.jsDSASystem DesignDevOpsCybersecurityAI / ML
Intermediate 20 min readModule: Module 9: Large Language Models (LLMs) & Prompt Engineering

LLM APIs, Sampling Parameters & Prompt Engineering

Master modern LLM APIs, sampling parameters (temperature, top_p), System prompts, and Few-Shot Chain-of-Thought reasoning.

What You Will Learn in This Lesson

  • How Autoregressive LLMs predict the next token probability distribution
  • Controlling randomness: Temperature (0.0 = deterministic, 1.0 = creative) and top_p
  • Advanced prompt techniques: Few-Shot In-Context Learning and Chain-of-Thought (CoT)

Introduction & Core Concept

Large Language Models (LLMs) are deep neural networks trained on vast corpora of internet text to generate human-quality text, write code, and perform multi-step reasoning.
WHY DOES THIS MATTER IN THE REAL WORLD?

Prompt engineering (adding structured instructions and few-shot examples) can boost model reasoning accuracy on complex tasks from 40% to over 85%.

Structured LLM Prompt Template

text
text
1
2
3
4
5
6
7
8
9
10
11
System: You are an expert code reviewer specializing in high-performance TypeScript.
 
User: Analyze this function for potential memory leaks.
Provide recommendations in valid JSON schema format:
{
  "hasLeak": boolean,
  "explanation": string,
  "fix": string
}
 
Assistant:

Line-by-Line Technical Breakdown

1Temperature 0.0 selects the argmax most probable token, ideal for deterministic code generation and SQL extraction.

Try It Yourself (Interactive Editor)

Modify the code in real-time and click Run to test live browser output and console logs.

Intelligent Code Runner & Live Sandbox[TEXT]
TEXT SOURCE EDITOR
Interactive Live Code

Industry Best Practices & Professional Standards

  • Use system messages to establish role boundaries and enforce structured JSON output.

Lesson Summary & Core Takeaways

  • Disciplined prompt engineering and parameter tuning extract peak capability from LLMs.