Prompt Engineering Guide
5 posts in this series
A prompt engineering path for structure, templates, roles, context, evaluation, cost control, and business scenarios.
Prompt Engineering in Practice: 10x Your AI Output Quality with These Techniques
Master 7 practical prompt optimization techniques to boost AI output quality. From vague instructions to structured tasks, covering writing, coding, and data analysis scenarios. Learn role prompting, chain-of-thought, few-shot learning, and more to double your ChatGPT and Claude results. Includes complete template library.
Prompt Engineering Advanced Practice: From Tricks to Methodology
From scattered tricks to systematic methodology, deep dive into Chain-of-Thought, ReAct, DSPy and other advanced techniques, master differentiated best practices for Claude and ChatGPT, build an evaluable and iterable Prompt engineering system
Prompt Engineering for Business: Customer Service, Sales, and Operations Guide
A practical guide to Prompt Engineering across three key business scenarios: customer service, sales, and operations. Includes real data, reusable Prompt templates, and a 7-step enterprise deployment framework to solve AI implementation challenges.
Prompt Engineering Template Library: 12 Reusable Prompt Design Patterns
A proven method for building a Prompt template library, including a four-field structure, 12 Prompt Patterns, multi-model adaptation table, and 5 production-ready templates that can be copied and used directly.
Why Prompt Caching Is Not Saving Money: Troubleshoot AI Coding Agents with prompt-cache-skills
Diagnose volatile prefixes, cache keys, disabled defaults, and short TTLs, then use prompt-cache-skills and cold-versus-warm requests to verify real cache hits.
