1292 related articles
Building AI Engineering Skills from Sc…
A deep dive into 'ai-engineering-from-scratch,' the GitHub project with 38K+ stars that helps developers build real AI engineering skills through a Learn-Build-Ship methodology.

A technical deep-dive into AI-assisted reverse engineering: how MCP, Skills libraries, and Frida toolchains work together, their real capability limits, and the legal boundaries of iOS/Android/Web reverse analysis.

Google engineer Addy Osmani's open-source project agent-skills (76k+ GitHub stars) injects production-grade engineering skills into AI coding agents, covering performance, security, and code quality.

GPT-5.6 SoulX High tops the frontend dev leaderboard at 1636 points with Agent Arena rank #2. Hands-on tests of portfolio pages and mystery games reveal its task decomposition and self-correction capabilities.

Deep dive into Harness Engineering: why AI Agents need memory management, durable execution, guardrails & approvals to go from demo to production.

Deep dive into Harness Engineering: why AI Agents need memory management, durable execution, guardrails & approvals to reach production. Based on Scott Moss's workshop.

Explore Harness Engineering: the next evolution beyond context engineering for AI programming. Learn how to build enterprise-grade Skill systems and deliver real projects with mid-tier models.

An open-source STEM education robot using Edge Impulse edge AI for local object detection, teaching kids computer vision and ML through an engaging ball-fetching game with anthropomorphic design.

A developer used Anthropic's Opus 5 model to build a No Man's Sky-style space exploration game in one day using Blender MCP and sub-agents. Deep dive into the technical architecture and industry implications.

OpenAI's Jason Liu shares how he uses ChatGPT Workbench and Codex to build an AI work OS: Chief of Staff automation, persistent threads, Skills/Plugins, browser control, and app-building methodology.

A systematic breakdown of the AI LLM learning roadmap covering prompt engineering, AI Agent development, RAG knowledge bases, model fine-tuning, and hands-on projects for beginners.

A systematic guide to AI Agent development from beginner to deployment, covering task planning, tool calling, memory management, learning paths, and realistic commercial monetization considerations.

Complete guide for backend developers transitioning to AI/LLM engineering. Covers the 4 core skills—Python, RAG, Fine-tuning, and Agents—with a phased learning roadmap and practical project advice.

Deep dive into Agent skill routing: comparing pure model vs. pure retrieval approaches, with a detailed two-stage layered architecture balancing accuracy, latency, and cost.

A deep dive into AI Agent Skills: understand the core concepts and technical implementation through the four key elements — SKILL.md, references, scripts, and assets — and learn how Skills differ from prompts.

A deep dive into AI Agent Skills: their core concepts, technical implementation, the four key elements (SKILL.md, references, scripts, assets), and how Skills differ from prompts.

A detailed guide to Vibe Coding with AI programming tools like Claude Code, Cursor, and Codex. Learn how to leverage AI-driven development to ship products independently and build lasting career value.

Deep dive into OpenAI GPT-5.6 Value Maxing strategies covering Sol/Terra/Luna model selection, KV cache optimization, Prompt compression, and programmatic tool calling to help developers achieve more output with fewer Tokens.

Deep dive into ChatGPT's plugin directory upgrade—how AI connects email, docs, calendars and more to transform from a chat tool into a workflow hub platform.

Deep dive into ChatGPT's plugin upgrade: how AI connects email, docs, calendars & more to transform from a chatbot into a workflow hub with cross-app aggregation.