Prompt Engineering Resources
A curated collection of the most valuable resources for learning and mastering prompt engineering techniques, frameworks, and best practices for AI-assisted development.
Technical Guides and Tutorials
Core Learning Resources
-
Prompt Engineering Guide - Prompt Engineering Guide, 2024
Comprehensive guide covering fundamental concepts and advanced techniques -
Prompt Engineering 101 for Developers - Pluralsight, 2024
Developer-focused introduction to prompt engineering fundamentals -
What is Prompt Engineering? A Detailed Guide For 2025 - DataCamp, 2025
Up-to-date overview of prompt engineering in the current AI landscape
Industry Perspectives
-
Prompt Engineering: Challenges, Strengths, and Its Place in Software Development's Future - InfoQ, 2024
Analysis of prompt engineering's role in modern software development -
6 Things to Know About Prompt Engineering in 2024 - Developer Nation, 2024
Key insights and trends in prompt engineering
Development-Specific Resources
-
Prompt Engineering for Coding Tasks - Towards Data Science, 2024
Specialized techniques for code generation and programming tasks -
3 Ways to Boost Your Prompt Engineering for AI-Assisted Programming - Open Data Science, 2024
Practical tips for improving AI-assisted coding workflows -
The Prompt Engineering Playbook for Programmers - Addy Osmani, 2024
Strategic approaches for developers using AI tools
Web Development Focus
-
Prompt Engineering for Web Development - SitePoint, 2024
Web-specific prompt engineering techniques and examples -
Prompt Engineering for Web Developers - 101 Blockchains, 2024
Blockchain and web3 development with AI assistance -
Prompt Engineering for Python Code Generation: Techniques and Best Practices - DEV Community, 2024
Python-specific prompt engineering strategies
Prompting Techniques and Methodologies
Core Techniques
Chain-of-Thought Prompting
-
Chain-of-Thought Prompting - Prompt Engineering Guide
Step-by-step reasoning approach for complex problem solving -
What is Chain of Thought (CoT) Prompting? - IBM, 2024
IBM's comprehensive explanation of CoT methodology
ReAct Framework
-
ReAct Prompting - Prompt Engineering Guide
Reasoning and Acting framework for enhanced AI interactions -
ReAct: A New Framework for Prompt Engineering in Large Language Models - Perxeive, 2024
Detailed analysis of the ReAct framework implementation -
ReAct Prompting: How We Prompt for High-Quality Results from LLMs - Width.ai, 2024
Practical guide to implementing ReAct prompting
Few-Shot Learning
- Few-Shot Prompting - Prompt Engineering Guide
Techniques for learning from limited examples
Advanced Methodologies
-
Prompt Engineering Techniques: Top 5 for 2025 - K2view, 2025
Latest techniques and emerging best practices -
A Complete Guide to Meta Prompting - PromptHub, 2024
Advanced meta-prompting strategies and applications -
Prompt Engineering - Lil'Log, 2023
Foundational technical deep-dive into prompt engineering
Framework and Infrastructure Resources
Context and Architecture
-
What is a Context Window? - IBM, 2024
Understanding context limitations and management -
Why Larger LLM Context Windows are All the Rage - IBM Research, 2024
Impact of expanding context capabilities -
Understanding the Impact of Increasing LLM Context Windows - Meibel, 2024
Practical implications of larger context windows
Developer Productivity
-
Measuring Impact of GitHub Copilot - GitHub Resources, 2024
Quantifying AI-assisted development productivity -
The SPACE Framework for Developer Productivity - Logilica, 2024
Measuring and improving developer productivity with AI tools
Benchmarks and Evaluation
-
14 Popular LLM Benchmarks to Know in 2025 - Analytics Vidhya, 2025
Current standards for evaluating language model performance -
FSE 2024 - Plenary Events - ESEC/FSE, 2024
Academic conference insights on software engineering and AI
Programming Language Comparisons
AI Framework Comparisons
-
PyTorch vs TensorFlow: Which is Better in 2024? - upGrad, 2024
Framework comparison for AI development -
PyTorch versus Tensorflow: Comparative Analysis of AI Frameworks - CUDO Compute, 2024
Technical analysis of leading AI frameworks -
PyTorch vs TensorFlow: Choosing Your Deep Learning Framework - F22 Labs, 2024
Decision guide for framework selection
Systems Programming
-
Go vs. Rust: When to Use Rust and When to Use Go - LogRocket Blog, 2024
Comparative analysis for systems programming -
Rust vs Go? Which Should You Learn in 2025 - DEV Community, 2025
Learning path recommendations -
Rust vs Go: Which One Should You Learn in 2025? - Peerlist, 2025
Career-focused language comparison
Language Trends
-
The Programming Languages Taking Over in 2024 and Beyond - Amoria Bond, 2024
Market trends and language adoption patterns -
Top 10 Mobile App Development Frameworks in 2024 - Bacancy Technology, 2024
Mobile development framework landscape
Research and Academic Resources
Comprehensive Studies
-
UMD Researchers Lead a Comprehensive Survey on Prompting Techniques - University of Maryland, 2024
Academic research on prompting methodologies -
The Prompt Report: Insights from The Most Comprehensive Study of Prompting Ever Done - Learn Prompting, 2024
Large-scale analysis of prompting effectiveness
Reference Materials
-
What is Prompt Engineering? Trend in 2024 - DE Academy, 2024
Industry trend analysis and future outlook -
Prompt Engineering - Wikipedia - Wikipedia
Comprehensive encyclopedia entry on prompt engineering
Getting Started
For beginners, we recommend starting with:
- Prompt Engineering Guide for foundational knowledge
- Few-Shot Prompting for practical techniques
- Chain-of-Thought Prompting for advanced reasoning
For developers specifically:
- Begin with Prompt Engineering 101 for Developers
- Explore The Prompt Engineering Playbook for Programmers
Contributing
This resource collection is continuously updated. If you have suggestions for additional resources or notice outdated links, please contribute to keeping this guide current and valuable for the community.
Last updated: June 12, 2025