Basic AI Prompts for Developers: Practical Examples for Everyday Tasks
Ready-to-use prompts that developers can integrate into their daily workflows, tested using Portkey's Prompt Engineering Studio
prompt engineering
Accelerating LLMs with Skeleton-of-Thought Prompting
A comprehensive guide to Skeleton-of-Thought (SoT), an innovative approach that accelerates LLM generation by up to 2.39× without model modifications. Learn how this parallel processing technique improves both speed and response quality through better content structuring.
Meta prompting: Enhancing LLM Performance
Learn how meta prompting enhances LLM performance by enabling self-referential prompt optimization. Discover its benefits, use cases, challenges, and how Portkey’s Engineering Studio helps streamline prompt creation for better AI outputs
Prompt Engineering for Stable Diffusion
Learn how to craft effective prompts for Stable Diffusion using prompt structuring, weighting, negative prompts, and more to generate high-quality AI images.
Understanding prompt engineering parameters
Learn how to optimize LLM outputs through strategic parameter settings. This practical guide explains temperature, top-p, max tokens, and other key parameters with real examples to help AI developers get precisely the responses they need for different use cases.
COSTAR Prompt Engineering: What It Is and Why It Matters
Discover how Costar prompt engineering brings structure and efficiency to AI development. Learn this systematic approach to creating better prompts that improve accuracy, reduce hallucinations, and lower costs across different language models.
Mastering role prompting: How to get the best responses from LLMs
Learn how to get better AI responses through role prompting. This guide shows developers how to make LLMs respond from specific expert perspectives with practical examples and best practices.