97 related articles

A deep dive into Loop Engineering for AI Agents — what loop feedback mechanisms are, how they differ from Harness Engineering, and a complete guide from principles to production implementation.

A comprehensive guide to Agent Skills: what Skills are, how they differ from Prompts, and how to design SKILL.md files. Learn modular AI Agent development through a real restaurant branding example.

Vercel's Chief of Software Andrew Qu explains the eve Agent framework's design philosophy, covering Skills modularity, Sandboxes security, and agent-readable websites—revealing the paradigm shift from instruction-driven to goal-driven software.

Andrew Ng and LangChain CEO Harrison Chase present AI Agents in LangGraph, covering five core agent design patterns and LangGraph's graph-based framework for building cyclical agentic workflows.

Andrew Ng and LangChain CEO Harrison Chase's AI Agents in LangGraph course covers five agent design patterns and LangGraph's graph-based framework for building cyclical AI workflows.

Generative AI is reshaping software development, shrinking demand for junior developer roles. This article analyzes why entry-level positions are most at risk, the talent pipeline implications, and how junior developers can leverage AI tools to stay competitive.
AI Tutor Achieves Effect Size of 1.30:…
Dartmouth's latest study shows an AI tutor system achieving 0.71–1.30 SD learning effect sizes in a real course, far exceeding most educational interventions. We examine what these numbers mean and why caution is still warranted.
AI Coding Addiction: The Hidden Price …
AI coding tools trigger dopamine-driven addiction loops, but skill atrophy, code comprehension gaps, and dulled judgment are quietly accumulating. A deep dive into the hidden costs.

A roundup of 12 trending open-source AI agent projects on GitHub, covering video generation, agent frameworks, skill packs, code engines, security scanning, and voice processing.
Payload-Less Skills: The Hidden Supply…
Payload-Less Skills are a stealthy new attack targeting LLM agent supply chains — no malicious code required. Learn how they work and how to defend against them.

App Builder generates single-file runnable apps from natural language, with real-time sandbox preview and conversational revision. Deep analysis of its workflow, architecture, limitations, and costs.
Has AI Coding Assistant Fable Been Ner…
A developer questioned whether AI coding assistant Fable was nerfed, finding 4–10x more tokens routed to Opus with Fable doing ~20% of the work. A deep dive into multi-model routing, transparency, and AI trust.

AI Agent autonomous programming is evolving from niche experiments to the industry default. This article analyzes the three stages of AI-assisted programming, its impact on developer skills, process restructuring, and key challenges.

OpenAI board member Zico Kolter and Gray Swan CEO Matt Fredrikson explain why AI safety differs fundamentally from cybersecurity and how red-teaming must evolve into a systematic engineering discipline.

Anthropic engineer Arno shares a Claude Code workflow: AI-driven requirements extraction, HTML specs over Markdown, and DOM-embedded verification to boost AI-assisted coding efficiency.

Veteran developer Mario Zechner dissects flaws in Cloud Code, OpenCode, and Cursor, then builds Pi — a minimalist coding Agent with just four tools and deep extensibility.

Ponytail is a minimalist plugin for Claude Code that uses YAGNI principles and a decision ladder to cut AI-generated bloat. Tests show 47%-77% cost savings and 94% less code.

A systematic guide to AI Agent development covering the three-stage learning path, core tech stack including LLM, RAG, and LangChain, plus how to build a one-person company through automated Agent workflows.
Deep DivesComplete guide to the three core LLM training stages: pre-training, supervised fine-tuning (SFT), and preference alignment (DPO/PPO), covering LoRA, distillation, quantization, and pruning.
Deep DivesDeep dive into Pi's swarm system architecture (26K GitHub stars): scout, worker, and soldier ant roles, pheromone communication, adaptive concurrency control, and how multi-agent collaboration revolutionizes AI programming.