#engineering methodology
1008 related articles
·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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·2 min
Harness Engineering: An Advanced Methodology for Programmers to Master AI Coding
From prompt engineering to context engineering to Harness engineering, this article breaks down the three evolutions of AI coding and offers engineering solutions to pain points like hallucinations, non-standard code, and infinite loops.
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·2 min
Harness Engineering: The Core Methodology for Enterprise-Grade AI Coding
From prompt engineering to Harness Engineering, a deep dive into the three-stage evolution of AI coding. Learn how enterprises use engineered frameworks to harness AI models for production-ready code.
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·2 min
Harness Engineering: The Core Methodology for Enterprise-Grade AI Coding
From prompt engineering to Harness Engineering: a deep dive into the three-stage evolution of AI coding. Learn how enterprises use engineering frameworks to harness LLMs and ship production-ready code.
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·2 min
Building a Slack-Native Coding Agent: Architecture Design and Engineering Methodology
A deep dive into embedding a coding agent in Slack: core architecture, permission design, async task handling, and RAG context management for AI-powered dev workflows.
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·3 min
AI Code Getting Worse with Every Fix? A Three-Layer Closed-Loop Engineering Methodology to Break the Cycle
AI code spiraling out of control? This article breaks down a three-layer engineering system — Prompt rules, Skill workflows, and Harness feedback loops — with real-world results showing pass rates rising from 70% to 98%.
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·2 min
AI Agents for SGLang Kernel Optimization: Real-World Performance Gains and Engineering Methodology
SGLang's team converted expert knowledge into agent skills, achieving 71.4% throughput gains, TTFT reduced from 456ms to 168ms. A deep dive into agent-assisted kernel optimization methodology.
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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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·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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·7 min
Harness Engineering: Core Methodology and Practical Guide for Enterprise-Level AI Programming
Can AI really replace programmers? This article explains Harness Engineering principles and its three evolutionary stages, revealing real pain points of enterprise AI programming.
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·3 min
Harness Engineering: The Core Methodology for Advanced AI Programming
Can zero-experience users replace programmers with AI tools? This article breaks down 4 core AI coding pain points and the 3-stage evolution from Prompt Engineering to Harness Engineering.
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·3 min
Claude Code + Harness AI Engineering in Practice: From Methodology to Enterprise-Level Implementation
Deep dive into Claude Code + Harness AI engineering methodology, covering tech stack selection, enterprise e-commerce implementation, task decomposition, and Prompt templatization.
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·3 min
The Vibe Coding Four-Module Framework: A Complete Methodology from Fragmented Learning to Engineering Delivery
A deep dive into the Vibe Coding four-module framework: paradigm cognition, open-source customization, SDD, and project rules for real engineering delivery.
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·3 min
Harness AI Engineering Programming: A Detailed Methodology for Enterprise-Level Project Development
Deep dive into Harness AI Engineering Programming methodology, covering SDD, Skill development patterns, and core practices for enterprise-level AI-assisted development.
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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·2 min
Harness AI Engineering: A Practical Methodology for AI-Assisted Programming in Enterprise Projects
Explore the Harness AI Engineering methodology for enterprise AI programming — solving code hallucinations, quality issues, and more with systematic human-AI collaboration.
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·2 min
Generating Zack Snyder-Style Movie Posters with AI: A Creative Experiment with a Single Prompt
Explore how a single AI prompt generates Zack Snyder-style movie posters. Analyzing style anchoring, prompt engineering, AI style transfer capabilities, and copyright ethics.
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·2 min
Generating Zack Snyder-Style Movie Posters with AI: A Creative Experiment with a Single Prompt
Explore how a single AI prompt generates Zack Snyder-style movie posters. A deep dive into style anchoring, prompt engineering, diffusion models' aesthetic transfer capabilities, and copyright ethics.
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