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
ai-fundamentals
16 articles tagged ai-fundamentals. 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.
The AI Agent Stack in 2026: Every Layer Explained
A complete breakdown of the AI agent stack in 2026. Foundation models, orchestration frameworks, tools, observability, vector databases, and deployment options.
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.
Agentic AI Explained: What It Actually Means in 2026
Agentic AI goes beyond chatbots. Real planning loops, tool use, and memory explained with examples from Claude Code, Devin, and Manus.
Prompt Engineering for Agents vs. Chatbots: What Changes and Why
How prompt engineering differs for AI agents vs chatbots. System prompts, tool definitions, ReAct, structured outputs, persistence, error handling.
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.
Single Agent vs Multi-Agent Systems: Which One Do You Need?
Single agent or multi-agent? This guide cuts through the hype and explains exactly when each architecture makes sense, with real examples from production.
Best LLM for AI Agents in 2026: Comparing Anthropic, OpenAI, Google, Meta, and xAI
Which LLM is actually best for building AI agents in 2026? Honest comparison of Claude 4, GPT-5, Gemini 2.5, Llama 4, and Grok 3 for agentic use cases.
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.
Open Source vs Proprietary AI Agents: Tradeoffs and Use Cases
Open source or proprietary AI agents? This guide covers cost, control, privacy, and customization tradeoffs to help you pick the right path for your stack.
How to Build a RAG Agent in 2026: A Step-by-Step Guide
A practical guide to building a retrieval-augmented generation agent: when to use RAG vs context window, vector DBs, chunking, and frameworks.
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 Observability: Tracing, Logging, and Debugging in 2026
How to instrument AI agents for production: distributed tracing, structured logging, LLM observability platforms, and practical debugging techniques that.
AI Agent Evaluation: Benchmarks, Custom Evals, and What Actually Matters
How to evaluate AI agents using SWE-bench, WebArena, GAIA, and custom evals. What the numbers mean, what they miss, and how to measure what matters.