#Prompt engineering
3823 related articles
Tech Frontiers·1 min
Tips from the Creator of Claude Code: Prompt Engineering Techniques and Efficient Workflow Guide
Claude Code creator Boris shares hands-on tips: from codebase Q&A to parallel workflows, covering Claude.MD config, prompt strategies, and SDK usage.
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Tech Frontiers·3 min
AI Test Development Learning Path: A Practical Guide from Prompt Engineering to RAG Knowledge Bases
A systematic AI test development learning path covering LLM fundamentals, prompt engineering, PyTest automation, RAG knowledge bases, and MCP tool chains to help QA engineers master AI-empowered testing.
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Tutorials·2 min
Introduction to Prompt Engineering: The Real Reason AI Can't Understand You
Why does AI always give irrelevant answers? This article explains prompt engineering fundamentals from the probabilistic prediction principles of LLMs, teaching you how to communicate effectively with AI.
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Tutorials·2 min
OpenAI Codex Hands-On Tutorial: A Complete Guide to Prompt Engineering, Agent Skills & Cloud Automation
Deep dive into OpenAI Codex's three core capabilities: prompt engineering for better code generation, agent skills for autonomous programming, and cloud automation for end-to-end CI/CD pipelines.
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Tutorials·2 min
Practical Guide to Prompt Engineering: Core Optimization Techniques and Pitfalls to Avoid in 2026
A 2026 practical guide to prompt engineering: format selection, system message priority, role setting, few-shot learning, structured output, and how to avoid common pitfalls.
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Tutorials·2 min
Harness AI Engineering Programming: A Practical Guide from Prompts to Mastering Engineering
Deep dive into Harness Engineering methodology covering the three-stage evolution from prompt engineering to context engineering to AI Agent mastery, with enterprise e-commerce project examples.
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Tutorials·3 min
AI Agent Prompt Engineering: A Practical Guide to the Three-Layer Architecture
A practical guide to AI Agent prompt engineering using a three-layer architecture: System Layer, Input Layer, and Action Layer — with n8n examples.
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Deep Dives·4 min
Five Core Concepts of AI Programming: A Complete Guide from Prompt to Harness Engineering
A clear breakdown of five core AI programming concepts — Prompt Engineering, Context Engineering, Agent, Skill, and Harness Engineering — with real-world use cases and advice for indie developers.
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Tutorials·4 min
Jimeng Seedance 2.0 Tutorial: Money-Saving Tips + Prompt Engineering Walkthrough
Complete guide to ByteDance's Jimeng Seedance 2.0: core features, membership savings strategies, and prompt techniques covering first-last frame mode, motion reference, character replacement, and video fusion.
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Deep Dives·3 min
How the Single Responsibility Principle Is Revolutionizing Prompt Engineering: A Modular AI Narrative Architecture Explained
Explore how the Singulari-Tea Codex open-source project applies the Single Responsibility Principle (SRP) to Prompt architecture design, building a modular AI narrative system optimized for Gemini 2.5 Pro.
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Deep Dives·4 min
Context Engineering Explained: The AI Paradigm Shift from Prompt to Context Engineering
Deep dive into Context Engineering: its core principles and practices. From Prompt Engineering to context design, orchestration, and optimization—exploring how Karpathy's new AI paradigm reshapes LLM app development and AI Agent construction.
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Tutorials·2 min
Prompt Engineering Skills Library: Best Practices for Claude/GPT/Gemini Multi-Model Prompting
Deep dive into the open-source prompt-engineering-skills project covering model-specific prompt patterns and best practices for Claude, ChatGPT GPT-5.5, Gemini, and more.
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Tutorials·4 min
A Practical Guide to Context Engineering: The Path from Prompt Engineering to Production-Grade AI Systems
A deep dive into Context Engineering: core concepts and key techniques including RAG, long-context management, and AI Agent context orchestration for building production-grade AI systems.
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Product Reviews·3 min
GSD-2 Open Source Project Deep Dive: How Meta-Prompting + Context Engineering Keep AI Agents Working Autonomously Without Drifting
Deep dive into GSD-2's three core technologies: meta-prompting, context engineering, and spec-driven development — solving the problem of AI agents drifting off-target during long tasks.
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Tutorials·3 min
74K Stars on GitHub: The Most Comprehensive Open-Source Learning Guide for Prompt Engineering, RAG & AI Agents
Deep dive into the 74K-star GitHub project Prompt Engineering Guide, covering prompt techniques, context engineering, RAG, AI Agents, and complete learning paths for developers.
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Tutorials·3 min
Using HTML Instead of Markdown: An Overlooked AI Output Format Optimization Technique in Prompt Engineering
An Anthropic Claude team member reveals: asking AI to output in HTML enables SVG diagrams, interactive components, and color coding that Markdown can't achieve. Learn the principles and practice.
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·2 min
How to Control Chrome Extension Release Timing: Two Precision Scheduling Strategies
How can Chrome extension developers precisely control release timing? Learn two strategies—staged releases and server-side feature flags—to align launches with business milestones.
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·4 min
RAG in Practice: Building a Million-Scale Medical Consultation AI System with Retrieval-Augmented Generation
Learn how to build a medical AI assistant using RAG covering 790 diseases and 1.7M consultation records, with complete implementation of knowledge base construction, vector retrieval, BERT fine-tuning, and recall-ranking optimization.
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·4 min
Microsoft Agent Framework in Practice: Building Enterprise-Grade AI Agents with .NET
A deep dive into Microsoft Agent Framework for building enterprise AI agents with .NET, covering tool calling, multi-agent orchestration, Qdrant RAG, and A2A, MCP, AGUI protocols.
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·3 min
SJTU's ARIS Framework: Making Research Agents Reliably Conduct Autonomous Science
Shanghai Jiao Tong University releases ARIS framework for reliable end-to-end research automation. Self-review loops, score thresholds, and human-in-the-loop design solve AI agent drift problems.
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