#prompt engineering
3374 related articles
The Craftsmanship of Prompt Engineerin…
·2 min
The Craftsmanship of Prompt Engineering: Countless Iterations Behind a Single Sentence
How the Dia Browser team's practice reveals Prompt Engineering evolving into a serious discipline. Explore how taste, craft, and care create production-grade AI experiences and real competitive moats.
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·4 min
The Four Stages of AI Engineering Evolution: From Prompt to Loop Engineering Explained
A systematic breakdown of the four stages of AI engineering: Prompt Engineering, Context Engineering, Runtime Environment Engineering, and Loop Engineering — with core logic, bottlenecks, and real-world use cases.
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·3 min
Agent Harness: A New AI Agent Paradigm from Prompt Engineering to Execution Environment Orchestration
Deep dive into Agent Harness Engineering: how loop execution and context isolation overcome the bottlenecks of prompt and context engineering in modern AI coding agents like Cursor.
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·3 min
Core Insights from Andrew Ng's Prompt Engineering Course: From Fundamentals to Practice
Deep dive into Andrew Ng's ChatGPT Prompt Engineering course: Base vs. Instruction Tuned LLMs, two core prompting principles, and practical developer methodologies.
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·3 min
The Complete Guide to Prompt Engineering: From Zero to Practical Application
A complete guide to learning Prompt Engineering, covering LLM selection, prompt writing techniques, zero-shot/few-shot prompting, chain of thought reasoning, and Python API development.
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·4 min
Agent Harness: The Paradigm Leap from Prompt Engineering to Harness Engineering
Deep dive into Agent Harness: tracing the paradigm evolution from Prompt Engineering to Context Engineering to Harness Engineering, and how loop-based architectures solve context loss in AI coding agents.
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·3 min
Key Takeaways from Andrew Ng × OpenAI's Prompt Engineering Course: Two Core Principles Explained
Deep dive into Andrew Ng & OpenAI's ChatGPT Prompt Engineering course: Base LLM vs instruction-tuned models, two core prompting principles, and API-first development thinking for developers.
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·2 min
Replit's AI Loops Workflow Explained: Multi-Agent Collaboration Replaces Prompt Engineering
Deep dive into Replit's AI Loops workflow: how orchestrators, parallel agents, and Computer Use Verifiers build automated closed-loop systems through multi-agent collaboration.
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Loop Engineering: The Paradigm Shift f…
·3 min
Loop Engineering: The Paradigm Shift from Prompt Engineering to Automated Programming Agents
Deep dive into Loop Engineering's five core components including worktree isolation, skill files, and sub-agent separation. Explore why loop design is harder than prompt engineering.
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·4 min
The 8 Core Modules of Prompt Engineering: A Complete Guide from Fundamentals to Advanced Techniques
A systematic breakdown of the 8 core modules of prompt engineering, covering fundamentals, CoT, Few-shot, prompt security, and real-world AI applications.
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·3 min
Prompt Template Design for Document Summarization: A Practical Guide to Three-Layer Progressive Prompt Engineering
A practical guide to three-layer progressive Prompt template design for document summarization, covering requirements analysis, architecture design, validation, and optimization — boosting information extraction completeness from 78% to 91%.
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·4 min
Core Methodology of Prompt Engineering: A Systematic Deep Dive from Principles to Practice
A deep dive into prompt engineering principles and core methodology. Master three keys to high-quality prompts: specific, rich, and unambiguous. Learn tuning techniques and advanced programming integration.
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Tutorials·4 min
Core Methodology of Prompt Engineering: Principles, Techniques, and Complete Practical Guide
Deep analysis of Prompt Engineering core methodology: from LLM principles to the three key principles of specific, rich, and unambiguous prompts, plus programming advantages in the AI era.
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Tutorials·3 min
Building AI Agents with Node.js: Replacing Prompt Engineering with Function Calls
Learn how to refactor a Node.js AI Agent using Function Calls instead of prompt engineering. Covers tool definition via JSON Schema, the Agent Loop, and key implementation details from analyzing Claude Code.
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Tutorials·1 min
Context Engineering Replaces Prompt Engineering: A Guide to Boosting Programming Efficiency with Claude Code
Learn how Context Engineering replaces Prompt Engineering to boost Claude Code efficiency. Build complex multi-Agent projects with zero coding using structured context files.
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Tutorials·3 min
Harness Engineering: A Practical Guide to AI Programming — From Prompts to Mastery
Explore the three stages of AI programming evolution: from Prompt Engineering to Context Engineering to Harness Engineering. Master enterprise-grade AI coding with Cloud Code + VS Code.
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Tutorials·3 min
Harness Engineering: A Practical Guide to AI Development — From Prompts to Mastering AI Agents
A deep dive into Harness Engineering's three-layer architecture: Information, Constraint, and Automation layers, covering Agent failure modes, OpenAI and Anthropic best practices, and AI tool selection strategies for controlled AI development.
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Tutorials·3 min
AI-Generated Data Visualization Dashboards: Prompt Engineering Best Practices and Iterative Development Techniques
Learn how to use prompt engineering to drive AI generation of commercial-grade visualization dashboards, covering layout and content descriptions plus iterative development strategies.
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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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