Agents on Fernando Ruiz

Agent vs. Assistant vs. Copilot: Three Ways to Delegate to AI

Mon, 01 Jan 0001 00:00:00 +0000

info Quick Definition

An AI assistant answers a request and leaves the next decision to the person. An AI copilot works alongside them inside their task and offers suggestions in context. An AI agent receives a goal, runs several steps with tools and only returns when it finishes or needs a human decision.

Where is the line?

The difference is not in the brand or the technology. It is in who runs the steps. In an assistant, the person does almost all the work and the AI answers. In a copilot, the person keeps carrying the work and the AI proposes the next step without taking it. In an agent, the AI decides and runs steps on its own, uses tools and adjusts what it does based on the results.

Claude Code: a programming agent that works in your repo

Mon, 01 Jan 0001 00:00:00 +0000

info Quick Definition

Claude Code is Anthropic’s programming agent. It reads your code, edits several files at once, runs commands and connects to external tools through MCP. It is used from the terminal, editor extensions, the desktop app or the browser, and it shares the same configuration across all of them.

What does it actually do?

Claude Code takes a task in natural language, for example “write tests for the authentication module, run them and fix the failures.” Then it plans, reads the files it needs, writes changes across several files and runs commands to verify them. It works directly with git: it stages changes, writes commit messages, creates branches and opens pull requests.

What Is an AI Agent?

Mon, 01 Jan 0001 00:00:00 +0000

info Quick Definition

An AI agent is a system in which a language model receives a goal, decides which steps to take, uses tools to act (read files, run commands, call services) and reviews the results until the task is finished or it stops.

What does it mean that it “decides” its steps?

A traditional chatbot answers a question with text and waits for the next one. An agent receives a task such as “fix the failing tests in the authentication module” and works out the order by itself: first it runs the tests, then it reads the files that fail, then it edits the code and finally runs the tests again to check.