📝Overview

The Prompt Engineering whitepaper—published by Google and featured on Kaggle—is a comprehensive guide (~65–69 pages) that treats prompt design as a disciplined engineering practice. Covering foundational techniques like zero-shot, few-shot, system and role prompts, it also dives into advanced methods such as Chain-of-Thought (CoT), ReAct, Self-Consistency, and Tree-of-Thought for improved reasoning and structured outputs. Authored by Lee Boonstra and other experts, it offers a structured taxonomy, practical tips, parameter tuning (temperature, top‑k/p), and real-world examples including code generation, medical summarization, and external tool usage. Positioned as a go-to manual, it bridges theoretical best practices with production-ready prompting workflows suitable for LLM integration across domains.

📚What You'll Learn

• Core prompting strategies (zero‑shot, few‑shot, system & role prompts) with clear comparative guidance.

• Techniques for enhanced reasoning and structure, such as Chain-of-Thought, Self‑Consistency, ReAct, and Tree‑of‑Thought.

• Parameter tuning and output formatting, covering temperature, top‑k/p, and JSON or structured outputs for reliable pipeline integration.

• Real-world usage examples spanning tasks like code generation, data extraction, medical summarization, and LLM-to-tool chaining.

👥Best For

• Engineers building AI-powered products using LLMs

• Technical leads designing agentic systems or automation workflows

• Teams evaluating whether to use tools like LangChain, or build from scratch

• AI architects looking to integrate tool use, memory, and dynamic decision-making

• Builders who want reliable, interpretable, and extensible LLM-based agents