#AI programming engineering
2803 related articles
Tutorials·1 min
5 Claude Code Skills I Use Daily: Taming AI Programming with Engineering Workflows
Deep dive into Matt Pocock's 5 daily Claude Code Skills: Grill Me for requirements, PRD generation, task decomposition, TDD, and code architecture optimization.
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Tutorials·2 min
AI Programming Post-Mortem: 6 Engineering Rules That Determine Project Success or Failure
Post-mortem from a real Android project built with AI tools, distilling 6 engineering rules—from cross-project context to local environment loops and API contracts—that determine AI programming success.
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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·2 min
Harness AI Engineering Programming: A Practical Guide to Building Enterprise-Grade Projects with Claude Code
A deep dive into the Harness AI Engineering Programming framework — how to use Claude Code with VS Code for enterprise-grade development, covering architecture, task decomposition, and quality gates.
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Product Reviews·2 min
Harness AI Engineering Programming: Boost Enterprise Project Development Efficiency by 10x
Deep dive into Harness AI engineering programming methodology, solving AI coding pain points like hallucinations, code standards, and context loss for 10x enterprise efficiency.
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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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Research·4 min
Skills-Oriented Programming: Domain Knowledge Engineering for Efficient Code Generation by Code Agents
Alibaba Mama's Skills-Oriented Programming methodology uses three-layer Skill structures, progressive disclosure, and four-layer anti-corruption systems to achieve 90%+ code generation accuracy for Code Agents in complex enterprise codebases.
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Expert Opinions·4 min
Rejecting Vibe Coding: Matt Pocock's Engineering-Driven Approach to AI Programming
TypeScript expert Matt Pocock's open-source Skills repo earned 80K+ GitHub Stars, using TDD and Domain-Driven Design to solve AI programming's three biggest pain points.
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Tutorials·3 min
Context Engineering: The Practical Method Replacing Vibe Coding to Double Your AI Programming Efficiency
Context Engineering is replacing Vibe Coding as the dominant AI programming methodology. Learn how to build high-quality context for AI coding assistants like Claude Code, with practical steps and open-source project insights.
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Tutorials·5 min
Claude Code Best Practices: What a 50K-Star Project Reveals About Engineering AI-Assisted Programming
Deep analysis of the 50K-star GitHub project claude-code-best-practice, covering the transition from Vibe Coding to Agentic Engineering with frameworks for context engineering, task orchestration, and iterative development.
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·3 min
AI Can't Build Usable Products — Developers' Jobs Haven't Disappeared
AI can generate code snippets and demos, but usable products still require human engineers' judgment and responsibility. This article analyzes AI coding tools' limits and developers' evolving roles.
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·2 min
General Agents Are Essentially Coding Agents: The Paradigm Shift from Tool Calling to Code Execution
Explore why general AI agents are essentially coding agents. From Turing completeness to composability and verifiability, discover the paradigm shift from Function Calling to Code as Action.
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·2 min
Anthropic's Call to Restrict Open-Source Models Sparks Outrage: Safety or Monopoly?
Anthropic CEO's call to restrict "dangerous capabilities" in open-source AI models sparks fierce backlash. Developers question double standards and fear monopoly disguised as safety.
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·3 min
Flint: A Deep Dive into the Visualization Language Optimized for AI Generation
Deep analysis of the Flint visualization language design philosophy, exploring how its declarative syntax and structured Schema optimize for LLM generation, enabling AI to efficiently create charts.
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·3 min
Composer 2.5 Real-World Review: Why a Budget AI Coding Assistant Became a Daily Go-To
A developer shares their real experience with Composer 2.5, from budget pick to daily go-to. Deep comparison with Sonnet 5 in debugging scenarios reveals the gap between benchmark scores and real productivity.
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·3 min
Composer 2.5 Real-World Review: Why a Budget AI Coding Assistant Became My Daily Driver
A developer shares their real experience with Composer 2.5, from budget pick to daily driver. Deep comparison with Sonnet 5 in debugging scenarios reveals the gap between benchmark scores and real productivity.
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·3 min
Self-Hosting a Code Review AI Agent: From Architecture Design to Engineering Implementation
A deep dive into building and self-hosting a code review AI Agent from scratch, covering architecture design, context management, model selection, and noise control.
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·5 min
Have AI Doomers Actually Used AI? A Developer Exposes the Gap Between Hype and Reality
AI Doomers warn AI will destroy humanity, but have they actually built AI apps? A developer's sharp critique reveals the vast gap between AI demos and real engineering practice.
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·3 min
Go Team Proposes Generic Collection Library 'container': A Deep Dive into the Standard Library Completion Plan
The Go team proposes new generic collection types under container/, including Set, ordered Map, queues, and more. A deep dive into the proposal and its design trade-offs.
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·3 min
Why We Abandoned Our LLM Router: Lessons in Over-Engineering
An in-depth analysis of why teams are abandoning LLM routers, exploring hidden complexity costs, outdated cost assumptions, and how to avoid over-engineering in AI systems.
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