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A detailed guide on using AI Agents to build Research Logs for scientific experiments, covering skeleton structure, daily workflows, pre-experiment thinking standards, code change tracking, and Agent-researcher division of labor.

How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.

Learn how to use AI Agents to build a Research Log for scientific experiments, covering structure, daily workflows, pre-experiment thinking, code change tracking, and human-AI division of labor.

Google DeepMind announces Gemini 4 pre-training has begun, calling it their most ambitious training yet. A deep dive into its technical direction, compute scale, multimodal breakthroughs, and competitive impact.

Poolside launches Laguna open-weight model after 18 months of silence, pitting 118B parameters against Kimi K3's 2.8 trillion. Can Silicon Valley's open-source push close the gap with Chinese AI?

Anthropic releases Claude Opus 5 with near-frontier performance at lower prices. Same day, Jensen Huang co-signs open-weight letter with 20+ companies while DeepSeek fundraising rumors surface.

Exploring the key evolution in coding agent architecture: separating the reasoning core from code execution environments to decouple control and execution planes.

Perplexity stuck in Computer Mode and can't switch back to normal search? This article analyzes the technical causes including server-side preference stickiness and platform differences, with practical solutions.

A developer added a DAW to their agentic dev environment with Claude, then paired with AI to finish music — experiencing a true AGI moment in creative collaboration.

Deep dive into the five evolution stages of AI Agent architecture: model calls, tool calls, workflows, Agent loops, and production runtime. Learn the responsibility boundaries and design principles.

A deep dive into Agent Skills architecture: modular design, progressive disclosure mechanism, and how it differs from Multi-Agent systems for AI capability extension.

Deep breakdown of 4 core AI Agent engineer competencies: business decomposition, multi-Agent architecture, quantitative evaluation, and engineering delivery—bridging the gap from Demo to production.

A systematic guide to AI Agent development across four stages: LLM fundamentals, ReAct paradigm, memory & tools, and multi-agent collaboration for developers.

Poolside releases its Laguna open-weight model after 18 months of silence, challenging Moonshot's Kimi K3 with 118B vs 2.8T parameters. Can Silicon Valley close the gap with Chinese AI?

Exploring the next evolution in coding agent architecture: decoupling the reasoning core from code execution environments to separate control and execution planes.

A detailed comparison of OpenAI Codex and Claude Code with hands-on testing. From AI agent concepts to account setup, helping developers quickly master AI coding agents.

A detailed guide to getting started with Codex and Claude Code AI agentic coding tools, from environment setup to hands-on practice, helping beginners master AI programming assistants.

A detailed guide to getting started with Codex and Claude Code—two leading AI agentic coding tools. From environment setup to hands-on practice, even beginners with no coding experience can master AI programming assistants.

An in-depth analysis of Jenkins' technical architecture, plugin ecosystem, distributed builds, and use cases — explaining why it remains the CI/CD leader.

An in-depth analysis of ag-kit, a TypeScript-based AI Agent development toolkit covering core architecture, modular design, use cases, and tech selection advice for full-stack developers.