#prompt engineering
2853 related articles
·3 min
Lessons from Claude Code's 80% Prompt Reduction: Less Is More in Prompt Engineering
Anthropic cut Claude Code's system prompt by 80% and got better performance. Learn why verbose prompts hurt, how to streamline them, and key takeaways for AI developers.
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·3 min
Lessons from Claude Code's 80% Prompt Reduction: Less Is More in Prompt Engineering
Anthropic cut Claude Code's system prompt by 80% and got better results. Learn why verbose prompts hurt performance, how to streamline them, and key lessons for AI developers.
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·5 min
Loop Engineering Explained: The New Programming Paradigm Where AI Prompts Itself
Loop Engineering is a paradigm shift in AI usage. Learn how to build automated loops where agents explore, execute, and verify tasks autonomously, with a hands-on e-commerce case study.
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·5 min
A Beginner's Guide to Prompt Engineering: From One-Off Instructions to a Systematic Methodology
A beginner's guide to prompt engineering covering the four functions of prompts, the key differences from prompt engineering, a six-step systematic workflow, and critical technical and practical limitations.
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·3 min
LoRA Fine-tuning or Prompt Engineering? Two Paths to Solving LLM Long-Conversation Memory
A developer fine-tunes a small model with LoRA to extract conversation state, tackling the LLM long-conversation memory problem. A deep dive into the technical approach, dataset design, and the real trade-offs between fine-tuning and prompt engineering.
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Cross-Model Prompt Engineering: Why Gr…
·3 min
Cross-Model Prompt Engineering: Why Great Prompting Techniques Work Universally
Explore why prompt engineering techniques transfer across AI models. Learn role definition, structured instructions, and Chain-of-Thought strategies that work universally across GPT, Claude, and beyond.
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·4 min
GPT-5.6 & OpenAI Super App Deep Dive: Loop Engineering as the New Paradigm Replacing Prompt Engineering
Deep dive into GPT-5.6 (Sol/Terra/Luna) and OpenAI's Super App: Loop Engineering, Parallel Agents, and Computer Use — unpacking the shift from prompt to loop engineering with real test cases and a startup framework.
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·3 min
GPT-5.6 Prompt Engineering in Practice: A Systematic Approach to Eliminating AI Verbosity
A deep dive into GPT-5.6's official eight-dimension prompt framework — tracing AI verbosity back to RLHF and training data, with practical constraint techniques to fix it.
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·1 min
Verbalized Sampling Lands at ICML: Does Prompt Engineering Belong at Top Conferences?
A prompt engineering paper on "verbalized sampling" accepted at ICML sparked fierce Reddit debate: does a prompting trick that mitigates mode collapse belong at a top ML conference?
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·5 min
From Prompts to Harness Engineering: The Evolution of AI Agent Development Paradigms
Why has AI engineering methodology evolved from prompts to context engineering and now Harness engineering? This article examines three paradigms, key bottlenecks, and the Agent = Model + Harness formula.
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·4 min
AI-Powered Automatic Environment Patching: JS Reverse Engineering with Sandbox + Prompt
Learn how to automate JavaScript reverse engineering environment patching with AI + sandbox. Three-step flow diagnoses missing BOM/DOM objects, generates patches, and self-validates. Get encrypted data in seconds.
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·6 min
Introduction to Prompt Engineering: Principles, Methods, and Practical Case Studies
Prompt Engineering is the core skill for harnessing LLMs. This article covers principles and design methods through real cases like translation role-setting and DeepSeek image generation.
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·6 min
Rust AI Agent System Prompt Engineering in Practice: A Seven-Dimensional Design Guide
An in-depth analysis of the four core roles of AI Agent system prompts and the four-step tool-calling method, covering behavioral boundaries, autonomous execution principles, and trigger pattern design—helping Rust developers build high-quality agents.
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·7 min
Andrew Ng's Prompt Engineering Course Essentials: Core Methodology Every Developer Must Learn
An in-depth analysis of the essentials of Andrew Ng and OpenAI's ChatGPT Prompt Engineering course. Covers the difference between base and instruction-tuned models, two core prompting principles, and how to wield LLM APIs to build apps.
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·6 min
Introduction to Prompt Engineering: A Complete Guide from Understanding to Implementation
Prompt engineering is more than messaging AI. This guide breaks down the four core functions of prompts, the six-step prompt engineering process, and key limitations to help you build the right foundation.
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·7 min
Prompt Engineering in Practice: A Programmer's Core Methodology for Prompt Tuning
A deep dive into the underlying logic of prompt engineering from a programmer's perspective: understand token-probability generation, master the three principles of specific, rich, and low-ambiguity, and learn iterative prompt tuning.
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·6 min
Prompt Engineering in Practice: A Programmer's Core Methodology for Tuning Prompts
An in-depth analysis of prompt engineering from a programmer's perspective: understand token probability generation, master the three principles—specific, rich, low-ambiguity—and learn iterative prompt tuning.
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·4 min
Prompt Engineering 101: Core Concepts, Value, and Limitations Explained
What is prompt engineering? This guide covers prompts, their four key functions, the 6-step engineering process, business value, and technical limitations for a complete foundation.
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·5 min
Introduction to Prompt Engineering: A Complete Guide to Core Concepts, Methodologies, and Limitations
Prompt engineering is a core skill in the AI era. This article breaks down the essential differences between prompts and prompt engineering, the six-step workflow, four evaluation criteria, and key limitations like context limits and hallucination.
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·3 min
Andrew Ng's Prompt Engineering Course: How Developers Call LLMs via API
A systematic overview of Andrew Ng's ChatGPT Prompt Engineering for Developers course: base vs. instruction-tuned models, API best practices, and two core prompting principles.
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