AI Concepts Articles
Browse 1364 articles about AI Concepts.
Open-Weight vs Closed AI Models: Why GLM 5.2 Changes the Cost Equation for Agents
Open-weight models like GLM 5.2 are closing the gap with frontier AI. Here's what that means for your agent stack and token budget.
What Is Seedance 2.5's Multimodal Reference System? 50 Inputs, One Consistent Video
Seedance 2.5 supports up to 50 image, video, and audio references in a single generation. Here's how the reference system works and when to use it.
What Is GLM 5.2? The Open-Weight Model With 1M Token Context for Agentic Workflows
GLM 5.2 is ZAI's flagship open-weight model with 1M token context, MCP support, and frontier-level coding at a fraction of the cost.
What Is GPT-5.6? OpenAI's Three-Tier Model System (Soul, Terra, Luna) Explained
GPT-5.6 introduces three model tiers: Soul for frontier work, Terra for everyday tasks, and Luna for high-volume cheap inference. Here's what each does.
What Is the Open Knowledge Format (OKF)? Google's Standard for AI Knowledge Bases
OKF is Google's open standard for building shareable LLM knowledge bases. Learn how it works, why it matters, and how to adopt it for your agents.
AI Model Selection Framework: Daily Driver vs Workhorse vs Specialist Models
Stop picking models by hype. Use this framework to match frontier models, open-weight workhorses, and specialist tools to the right tasks in your stack.
Claude Code /goal vs /routines vs /loop: Which Autonomous Scheduling Method Should You Use?
Claude Code offers three ways to run agents autonomously: /goal for completion conditions, /loop for intervals, and /routines for cloud-based cron jobs.
Claude Sonnet 5 Token Efficiency Problem: Why It Can Cost More Than Opus 4.8 in Agents
Claude Sonnet 5 uses 30% more tokens than other models due to its agentic design. Learn when it costs more than Opus and how to manage usage.
How to Build an OKF Knowledge Bundle: Share Your AI Knowledge Base with Any Agent
Google's Open Knowledge Format lets you package knowledge bases as shareable bundles. Learn how to build one and import it into your second brain.
How to Prompt Claude Fable 5 Like an Anthropic Engineer: 6 Rules That Actually Work
Anthropic's own best practices for Claude Fable 5 include giving context, negative prompting, effort levels, and avoiding reasoning requests that trigger Opus.
Human-in-the-Loop Checkpoints for AI Agents: Why Full Autonomy Is the Wrong Goal
The best AI agent workflows aren't fully autonomous—they have human checkpoints at the right moments. Here's how to design them into your systems.
Open-Weight AI Models vs Closed Frontier Models: How to Choose for Your Agent Stack
GLM 5.2, Qwen, and DeepSeek are catching up to Claude and GPT. Learn when open-weight models win and when frontier models are worth the cost.
What Is Claude Sonnet 5? Anthropic's Most Agentic Sonnet Model Explained
Claude Sonnet 5 is Anthropic's most agentic Sonnet yet—faster and cheaper than Opus 4.8 while matching it on most tasks. Here's what changed.
What Is Gemini Omni Flash? Google's Conversational Video Editing Model Explained
Gemini Omni Flash is Google's multimodal video model that lets you edit video through conversation—changing characters, lighting, and style iteratively.
What Is GLM 5.2? The Open-Weight Model With 1M Token Context and Frontier-Level Coding
GLM 5.2 is ZAI's 753B open-weight model with 1M token context, MCP support, and agentic coding at 1/5th the cost of frontier models.
What Is the Open Knowledge Format (OKF)? Google's Standard for Shareable AI Knowledge Bases
OKF is Google's open standard for LLM wikis—a minimal layer on top of Karpathy's knowledge base pattern that makes wikis shareable across AI agents.
The AI Context War: Why Siri, Claude Tag, and Codex Are Solving the Same Problem
Apple, Anthropic, and OpenAI are all racing to connect AI to your real-world context. Here's why context access matters more than model intelligence.
AI Model Export Controls Explained: What Government Review Means for Your AI Stack
The US government is reviewing frontier AI models before release. Here's what that means for builders who depend on Claude, GPT, and other models.
Human-in-the-Loop Checkpoints for AI Agents: Why Full Autonomy Is the Wrong Goal
Full AI autonomy creates quality problems. Learn how to design human checkpoints at the right moments to get leverage without losing control.
Multi-Perspective AI Research: How Sub-Agents Beat Single-Prompt Deep Research
Using 5 expert sub-agents for research produces better results than 100+ parallel agents. Here's the architecture and why it works for AI workflows.