120 related articles
The Evolution of Coding Agents: A Para…
Coding agents are evolving from reactive code completers to proactive planners. Explore the "think ahead of time" paradigm, Plan-and-Execute architecture, and its impact on developer workflows.

OpenAI's new model reportedly proved the Cycle Double Cover Conjecture in under an hour using 64 parallel sub-agents. The real lesson? In the AI era, knowing how to ask the right questions matters more than knowing how to calculate.

A deep dive into building verifiable, self-evolving Agent automation loops with Claude Code and Codex — covering Loop Contracts, four trigger types, three-phase execution architecture, and Evolve Loops.

A deep dive into AI-powered testing: Cursor Skills, Coze agents, and LangChain multi-agent systems for automated test case generation, BDD, and review workflows.

Andrew Ng partners with JetBrains to launch a Spec-Driven Development course, teaching how to direct AI coding agents via spec files to boost intent fidelity and build maintainable production apps.

What is an AI Agent's harness? This article systematically dissects the core components of agent frameworks: context management, tool use, control loops, and caching strategies—revealing why the same model performs so differently across harnesses.

Superpowers is a trending GitHub project that builds an agentic skills framework with Shell scripts, injecting software engineering methodology into AI coding workflows. A deep dive into its architecture and value.

When an intern uses AI to generate professional-looking slop code, stand-ups balloon from 15 to 45 minutes. This article dissects why AI slop is hard to spot and offers practical team solutions.

Vibe Coding saves time but leaves piles of bugs? This article details the cross-model review workflow: Claude generates, Codex auto-reviews, with Stop Hook and Skill mechanisms building an AI code review system that intercepts problems automatically.

Cursor launches deep Notion integration via the Cursor SDK — @mention Cursor in any Notion doc to trigger a cloud Agent that automatically opens a PR. We break down the workflow, product logic, and real-world limitations.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.