AI Tools Glossary 2026: Every Term You Actually Need to Know
A-to-Z reference of AI, ML, and agent terminology. Clear definitions for LLMs, RAG, diffusion, embeddings, tokens, XAI, and 60+ more terms.
Tag
explainer
15 articles tagged explainer. Browse the full blog.
When to Use AI Agents vs Workflows in 2026
A practical guide to choosing between dynamic AI agents and deterministic workflows, grounded in Anthropic's framing on when each model is the right fit.
What Is MCP (Model Context Protocol)? A 2026 Guide
A plain-English explainer of MCP (Model Context Protocol): what it is, how the architecture works, which servers are worth using, and where the standard.
What Is an AI Agent? A 2026 Plain-English Guide
What separates an AI agent from a chatbot, and why everyone's talking about them in 2026. Plain-English explainer with examples.
AI Agent vs Assistant vs Copilot: What's the Actual Difference?
The terminology is a mess. Here's a clear breakdown of what separates an AI agent from an assistant from a copilot, with real product examples.
What Is an Agentic Workflow? Definitions, Examples, Patterns
A plain-English guide to agentic workflows: what they are, how they differ from traditional automation, the patterns that matter, and when to actually use them.
AI Agent Context Windows Explained: Why They Matter in 2026
What context windows are, current sizes across Claude, GPT-5, and Gemini, and how agents manage long context. Plain-English guide for 2026.
Tool Calling in LLMs Explained: How AI Agents Use External Functions
A clear breakdown of tool calling in LLMs: what it is, how JSON schema works, how structured outputs work, and why function calling is what separates a.
The ReAct Pattern Explained: How AI Agents Reason and Act
A deep dive into the ReAct pattern (Reason + Act): the foundational LLM agent loop that powers most production AI agents, how it differs from.
RAG vs Agents: When to Use Each in 2026
RAG fetches knowledge. Agents take action. This guide explains the real difference, when each approach fits, and how agentic RAG combines them for harder.
How Do AI Agents Actually Work? Inside the Loop
A technical-but-accessible breakdown of how AI agents reason, plan, use tools, and remember things. From the basic loop to ReAct and real-world examples.
Function Calling vs MCP: How They Differ and When to Use Each
Function calling and MCP both let AI models use tools, but they solve different problems at different layers. This guide explains the real differences and.
AI Agents vs LLMs: What's the Real Difference in 2026?
LLMs generate text. Agents act on the world. This guide explains the real architectural difference, when each is the right tool, and how they work together.
AI Agents vs Chatbots: How They Differ in 2026
AI agents and chatbots are not the same thing. This guide breaks down how they work, where each one fits, and how to choose the right tool for your situation.
AI Agent Memory Systems Explained: Short-Term, Long-Term, Vector Stores
A deep dive into how AI agents remember things: short-term context windows, long-term storage, episodic vs semantic memory, vector databases, and.