How To Use AI

Reactive agents are fast. Goal-based agents plan. Utility-based agents optimize. Learning agents adapt. Autonomous agents do all of the above. Understanding the types of AI agents builds the judgment to pick the right tool for the right problem. ▶ Table of Contents (click to expand) If You Had to Pick an AI Agent Right Now, What Would You Choose? Classifying AI Agents — Two Questions That Separate Them All Reactive Agent — No Memory, But the Fastest of All Goal-Based Agent — The First Type That Can Plan Utility-Based Agent — Picks the Better Option, Not Just Any Option Learning Agent — Gets Smarter the More You Use It Autonomous Agent — Give It a Goal, It Figures Out the Rest All Six Types of AI Agents at a Glance Choosing an Agent — Why "Start Simple" Is Good Advice Wrapping Up — Know the Types of ...

Series Part 2 | Level: Beginner | 2026-06-03 — We open the hood on AI agents: agentic loop, ReAct, Chain of Thought, Tree of Thoughts, tool use, and memory systems — all explained from first principles. ▶ Table of Contents (click to expand) Quick Recap from Part 1 The Three-Beat Rhythm of Every AI Agent The Agentic Loop — The Heartbeat That Never Stops Think, Act, Observe — The ReAct Framework The Reasoning Engine — Chain of Thought and Tree of Thoughts Tool Use — A 5-Step Process Under the Hood Memory Systems — How AI Agents Remember A Real Example — Paris Cycling Trip Planner Key Takeaways Quick Recap from Part 1 In Part 1, we answered "What is an AI agent?" — and found that unlike a chatbot that simply responds, an AI ag...

Bottom line: An AI agent isn't just a chatbot that answers questions. It receives a goal, builds its own plan, uses tools to act, reflects on results, and keeps iterating until the task is done — all autonomously, without waiting for human direction. ▶ Table of Contents (click to expand) What Exactly Is an AI Agent? The 5 Core Components of an AI Agent AI Agent vs. Chatbot: What's the Real Difference? How Does an AI Agent Actually Work? Where AI Agents Are Being Used Right Now The Honest Limitations of AI Agents The One-Sentence Definition What Exactly Is an AI Agent? An AI agent is a software program that perceives its environment, gathers data, and automatically performs multi-step tasks to achieve a predefined goal — without waiting for a human to direct each move. AWS defines it as "an artificial entity that perceives its environment, makes decisions, and takes act...

As a network engineer who has been using both tools for a while now, I get this question a lot: Antigravity or Claude Code — which one should I use? Having tried both, my honest answer is: it depends on how you work. This post lays out the real differences between the two tools and helps you figure out which fits your situation — including a method I've been using myself: running Claude Code as an extension inside Antigravity. ▶ Table of Contents (click to expand) GUI IDE Comparison — The Fundamental Difference Between the Two Approaches Real-World Performance Differences — Strengths and Weaknesses Revealed in Testing Using Claude Code as an Extension — How to Use Claude Inside Antigravity's Chat Panel Choosing the Right Tool — Criteria by Situation Q&A — Frequently Asked Questions Conclusion GUI IDE Comparison ...

As a network engineer, MCP reminded me of SNMP — a standard protocol that lets different systems talk to each other in a unified way. MCP stands for Model Context Protocol, and it does something similar for AI agents: it lets them connect to external tools and data through a single standard. When I connected MCP to Antigravity, the AI became noticeably more accurate. This post explains what MCP is and how to set it up, in plain terms. ▶ Table of Contents (click to expand) What Is MCP — The Standard Protocol That Expands AI Agent Capabilities Providing a Codebase Map — How to Make the AI Understand Your Entire Project Advanced Agent Setup — Customizing Antigravity with MCP Q&A — Frequently Asked Questions Conclusion What Is MCP — The Standard Protocol That Expands AI Agent Capabilities A basic AI coding agent can only see ...