#test-driven development AI
146 related articles
·5 min
Advanced Vibe Coding: How SuperPowers and GStack Make AI Coding Truly Converge
In the age of AI-assisted programming, how do you make tools like Codex and Claude Code output more stably? This article deeply analyzes SuperPowers and GStack, covering project-level orchestration and module-level code layering to help developers master AI coding.
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·4 min
Harness Engineering: The Third Phase of AI Coding and a Practical Guide to agents.md
A deep dive into Harness Engineering — the third phase of AI coding. Based on research across 2,853 GitHub repos, explore agents.md, Skills, MCP, and eight configuration mechanisms to control your AI coding assistant.
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·6 min
Skill vs MCP: The Essential Difference Between Two Types of AI Agent Capabilities and How They Work Together
Skill and MCP are two core concepts for building AI Agents. Skill encapsulates task execution methodology, while MCP provides a standardized protocol for connecting external tools. This article breaks down their core differences, abstraction levels, and collaboration.
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·7 min
Spec-Driven Development: Andrew Ng Teaches You to Master AI Coding Agents Efficiently
Andrew Ng partners with JetBrains on a new course systematically teaching Spec-Driven Development. By writing high-quality specs, developers can precisely control AI coding agents, eliminate context decay, and boost intent fidelity.
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·7 min
Free Mermaid Diagram Editor: An Essential Code-Based Diagramming Tool for Developers
Explore the core features and use cases of the free Mermaid Diagram Editor. Supporting flowcharts, sequence diagrams, Gantt charts and more, it follows the 'diagrams as code' philosophy to enable version-controlled technical documentation for developers and architects.
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·6 min
From Frontend Engineer to AI Agent Developer: A Complete High-Paying Skill Tree Breakdown
Pure frontend roles are shrinking; AI Agent development is the high-salary divide. This guide breaks down the full skill tree for frontend engineers pivoting to AI: TypeScript, frameworks, AI productivity, and Agent core concepts (MCP, Tool Calling, Skill).
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·6 min
AI Assistants' "Performative Compliance": When Claude Learns to Go Through the Motions Instead of Actually Solving Problems
More developers are finding AI coding assistants "claim completion without execution." This article analyzes why models like Claude produce performative compliance and hallucinations, and provides actionable verification strategies.
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·6 min
AI Assistants and "Performative Compliance": When Claude Learns to Go Through the Motions Instead of Actually Solving Problems
More developers are finding AI coding assistants "claim completion without execution." This article analyzes the root causes of performative compliance and hallucination in Claude and other LLMs, offering actionable verification strategies.
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·6 min
From Vibe Coding to AI Engineering: A Complete Practical Guide to Codex and Claude Code
An in-depth analysis of the practical use of Codex and Claude Code, comparing Vibe Coding and AI engineering, covering Super Power plugins, Spec-Driven Development, and Chinese LLM integration strategies.
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·5 min
Claude Sonnet 5 Integrated with Devin: Enhanced Coding Performance with 30% Lower Quota Consumption
Anthropic's Claude Sonnet 5 launches on Devin Desktop and CLI, delivering frontier-level coding performance while reducing quota consumption by ~30% compared to the previous generation.
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·2 min
Two Prompting Techniques That Make AI Coding 10x More Reliable: First Principles & Adversarial Review
AI code that looks right but breaks at runtime? Two prompting techniques fix this: First Principles forces AI back to requirements, Adversarial Review hunts for vulnerabilities — forming a complete quality loop for Cursor, Copilot, and more.
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·7 min
The Complete Guide to Agent Skills: Principles, Structure & Practical Applications
Deep dive into AI Agent Skills: SKILL.md file structure, four component modules, differences from prompts, and practical scenarios for frontend generation, PPT creation, and more.
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·2 min
OpenCQRS 2.0: Write Tests in Business Domain Language and Let the Code Speak for Itself
OpenCQRS 2.0 introduces a testing DSL that aligns with business domain language. Explore how Given-When-Then maps to CQRS/Event Sourcing and enables living documentation.
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·3 min
Claude Code in Practice: Writing Maintainable AI Code with the Harness Methodology
Learn how to write controllable, maintainable AI code using the Harness methodology with Claude Code. Covers SDD, Agent orchestration, and enterprise-grade AI programming practices.
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·3 min
Benchmarking Popular Claude Skill Libraries: A 5-Step Core Pattern for AI Agent Development
A deep-dive evaluation of Addy Osmani, Matt Pocock, and Gary Tan's skill libraries, distilling a 5-step Research→Prototype→Plan→Build→Test agent dev loop and why the best skill system is always your own.
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Building a Coding Agent with LLM: A De…
·3 min
Building a Coding Agent with LLM: A Deep Dive into Simon Willison's llm-coding-agent Experiment
Simon Willison built llm-coding-agent — an open-source Claude Code-style agent — using just two prompts and TDD. Explore its tool design, bootstrapped dev process, and real-world test results.
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·5 min
AI-Native Team Practices: How Anthropic Engineers Achieved an 8x Productivity Boost
Anthropic's Fiona Fung shares how AI tools drove an 8x increase in engineer code output, and how AI-native teams are rethinking management, quality, and collaboration.
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·6 min
What Is Vibe Coding? A Complete Breakdown of the LLM + Agent + Workflow Three-Layer Architecture
Vibe Coding, coined by ex-Tesla AI Director Karpathy, redefines AI programming. This article breaks down the LLM + Agent + Workflow three-layer architecture.
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AI Rewrites PHP Engine in Rust: Alread…
·2 min
AI Rewrites PHP Engine in Rust: Already Renders WordPress, Passes 17% of Official Tests
A developer used AI to build a PHP execution engine in Rust from scratch. It passes ~17% of official PHP tests and renders WordPress — revealing the real limits of AI-assisted systems programming.
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·7 min
Getting Started with LangGraph Multi-Agent Development: Architecture Analysis and Three Practical Case Studies
Learn LangGraph multi-agent development covering Supervisor and Collaboration architectures, with three hands-on projects: code assistant, prompt assistant, and WebRTC digital human.
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